System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting story text; means for automatically generating cartoon illustrations and text based on the story text utilizing a generative AI model; means for providing an interface through which a user can make modifications and additions; means for translating the generated cartoon into multiple languages; and means for publishing the generated and modified cartoon.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Traditionally, creating manga required advanced drawing skills, and many people gave up on creating manga despite having story ideas because they couldn't draw. Publishing in multiple languages ​​and monetizing the work also required specialized knowledge and a great deal of effort. There is a need for a system that solves these issues and allows even those who can't draw to easily create and publish manga. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that includes a means for inputting story text, a means for automatically generating illustrations and characters for a manga based on the story text using a generative AI model, a means for providing an interface that allows users to make corrections and additions, a means for translating the generated manga into multiple languages, and a means for publishing the generated and modified manga. Furthermore, by including a means for saving and managing the generated manga, and a means for placing advertisements and providing revenue data to users, the system simplifies the entire process from creating manga to publishing it in multiple languages ​​and monetizing it.

[0006] "Story text" is a sentence entered by the user that contains the content and details of the story.

[0007] A "generative AI model" is an artificial intelligence algorithm that automatically generates manga illustrations and text based on input story text.

[0008] The "modification and addition interface" is a user interface that allows the user to edit the content of the generated comic and make changes or additions.

[0009] "Translation means" is a function that automatically translates the generated manga into other languages.

[0010] "Publication means" refers to the function of making the created and edited manga available to the public through online platforms, etc.

[0011] "Storage and management means" refers to the function of saving the generated manga as digital data and managing it in a state that allows it to be used or edited later.

[0012] The "advertising placement means" is a function for placing advertisements in published comics and providing the revenue generated to users. [Brief explanation of the drawings]

[0013] [Figure 1]1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0014] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0017] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0018] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0019] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0026] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0033] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0034] This invention is a system that allows users who cannot draw to easily create and publish manga. The system is composed of the following main components: a means for inputting story text, a means for automatically generating manga using a generative AI model, an interface for users to make corrections and additions, a means for translating the generated manga into multiple languages, and a means for publishing the generated and modified manga.

[0035] Story text input

[0036] A user accesses the story input module of the system using a terminal (PC, smartphone, etc.). The interface provides a text area where the user can input their own story or scenario. Let's say that a user wants to input a story about a boy's adventure of defeating enemies with magical powers into this text area.

[0037] Generative AI Models

[0038] The server receives the story text entered by the user and passes it to the generative AI model. The generative AI model uses natural language processing (NLP) technology to analyze the story text and generate illustrations and text corresponding to each scene. Character designs and backgrounds are also automatically created. As a result, each page of the manga is automatically generated.

[0039] User-modified and added interface

[0040] The generated manga is displayed to the user from the server. The user can check the displayed manga and make corrections or additions as necessary. For example, they can change the lines of the characters or replace the background. The interface is designed to allow easy editing with drag-and-drop and click operations. Once the user has completed their corrections and additions, the data is sent to the server and the updated manga data is saved.

[0041] Translation Module

[0042] If a user wishes to publish in multiple languages, the server uses a translation module to translate the manga into the specified language. This module uses an AI-based translation engine to translate the text portion of the manga into other languages. The translation results are then incorporated back into the manga, generating multilingual manga data.

[0043] Publishing and Monetizing Your Manga

[0044] Once a user has completed their manga and indicates their intention to publish it, the server uploads the manga data to the publishing platform. The platform also provides the ability to insert advertisements to generate revenue. After publishing, users can check their revenue data on a dedicated dashboard.

[0045] As a concrete example, User A inputs a story called "The adventure of a boy who defeats enemies with the power of magic," and the generative AI model automatically generates a manga. User A then edits the characters' lines and adds additional background. User A then translates the manga into English and publishes it in multiple languages. User A can check the revenue generated from the published manga on the dashboard and earn revenue.

[0046] In this way, the present invention automates the manga production process and provides a system that allows anyone to easily create, publish, and monetize high-quality manga.

[0047] The processing flow will be explained below.

[0048] Step 1:

[0049] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs the story text into the text area. For example, the user inputs a story titled "A boy's adventure to defeat enemies with magical powers."

[0050] Step 2:

[0051] The device sends the story text entered by the user to the server. When the send button is pressed, the data is transferred using JavaScript or Ajax.

[0052] Step 3:

[0053] The server receives the story text and stores it in a database in an appropriate format, preparing it for input to the generative AI model.

[0054] Step 4:

[0055] The server inputs the saved story text into a generative AI model, which then analyzes the story. Using natural language processing technology, the AI ​​model divides the story into scenes and generates illustrations and text corresponding to each scene.

[0056] Step 5:

[0057] The server receives the generated manga data (images and text corresponding to multiple scenes) and stores it in the database again, where a series of pages are formed as a manga.

[0058] Step 6:

[0059] The server generates links and views to display the generated manga data to the user and notifies the user. The user then views a screen on their device where they can check the generated manga.

[0060] Step 7:

[0061] Users can use the provided editing interface to modify or add to the manga, such as changing or adding character lines, backgrounds, character designs, etc.

[0062] Step 8:

[0063] The device sends the user's modifications and additions to the server, and after the changes are confirmed in the form or interface, the data is transferred again using JavaScript or Ajax.

[0064] Step 9:

[0065] The server processes the received modifications and additions and merges them with the original comic data, updating the existing comic data in the database.

[0066] Step 10:

[0067] The server then displays the updated manga data to the user again, allowing the user to check it with any corrections or additions reflected.

[0068] Step 11:

[0069] If the user wishes to publish in multiple languages, he or she can select the desired translation language in the interface, for example, "English."

[0070] Step 12:

[0071] The device sends a translation request to the server along with information about the selected translation language. The user's selection is communicated to the server using JavaScript or Ajax.

[0072] Step 13:

[0073] The server retrieves the manga data and inputs it into the translation module, which extracts the text from the manga and passes it to the translation engine.

[0074] Step 14:

[0075] The translation module automatically translates text into a specified language. It uses an AI-based translation engine to translate text.

[0076] Step 15:

[0077] The server then incorporates the translated text into the original manga and saves it again, creating manga data in the new language and saving it in the database.

[0078] Step 16:

[0079] The server displays the translated manga to the user, who can then view the translated manga on their device.

[0080] Step 17:

[0081] When a user indicates their intention to publish a completed manga, they press the publish button on their device, and a publish request is sent to the server.

[0082] Step 18:

[0083] The device sends a disclosure request to the server, and the data required for disclosure is sent.

[0084] Step 19:

[0085] The server receives the publishing request and uploads the manga data to the publishing platform, along with metadata such as title, summary, and tags.

[0086] Step 20:

[0087] The server performs functions to place advertisements and provide revenue data to users. It embeds advertisements in published comics and reflects revenue information on the dashboard.

[0088] Step 21:

[0089] Users can check their earnings on their device and view how much advertising revenue they are earning through a dashboard.

[0090] The above are the specific processing steps of the system.

[0091] Example 1

[0092] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0093] Conventional manga production methods require advanced drawing skills and time, making it difficult for users who cannot draw to easily create manga. In addition, the process of publishing manga in multiple languages ​​and monetizing them is complicated, so a system that can be easily used by general users is needed.

[0094] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0095] In this invention, the server includes an input device for inputting story text created by the user, a generation device for automatically generating illustrations and text for a manga based on the story text using a generative AI model, a display device for providing an editing interface that allows the user to make corrections and additions to the generated manga, a translation device for translating the generated manga into multiple languages, and a publishing device for publishing the generated and revised manga based on the user's specifications. This allows users to easily create high-quality manga, publish it in multiple languages, and monetize it.

[0096] An "input device" is a means by which a user inputs story text that the user has created into the system.

[0097] A "generation device" is a means for automatically generating manga illustrations and text based on story text entered by a user, using a generative AI model.

[0098] An "editing interface" is a means for providing an interface that allows a user to make corrections or additions to the generated comic.

[0099] A "display device" is a device that provides a means for a user to review and edit the generated comic.

[0100] A "translation device" is a means for translating the generated manga into multiple languages.

[0101] The "publishing device" is a means for publishing the created and modified comic book based on the user's specifications.

[0102] A "storage device" is a means for storing and managing the generated comics.

[0103] The "profit device" is a means for placing advertisements and providing users with profit data for published comics.

[0104] A "generative AI model" is an artificial intelligence model that uses natural language processing technology to analyze story text and automatically generate manga illustrations and characters.

[0105] A "prompt sentence" is an input text that instructs a generative AI model to obtain a specific output.

[0106] This invention is a system that enables users who cannot draw to easily create and publish high-quality manga. The system allows users to input story text, and a generative AI model automatically generates a manga based on that text. The system also supports the user in a series of processes to modify, add to, translate, publish, and monetize the manga.

[0107] First, a user accesses the system using their own device (PC, smartphone, etc.) and inputs story text into the story input module. For example, they input a story such as "A boy's adventure of defeating enemies with magical powers."

[0108] The server then receives the story text entered by the user and sends the data to a generative AI model, which uses natural language processing (NLP) techniques to analyze the story text and generate illustrations and characters corresponding to each scene. This automatically creates character designs and backgrounds, generating each page of the manga.

[0109] The generated manga is displayed on the user's device via the server. The user can review the displayed manga and make corrections or additions. For example, they can change the dialogue of characters or add new backgrounds. The editing interface is designed for easy use with drag-and-drop and click operations.

[0110] Furthermore, if a user wants to publish a manga in multiple languages, the server will translate the manga into the specified language using a translation module, which utilizes an AI-based translation engine to convert the text of the manga into other languages.

[0111] Finally, once the user has indicated their intention to publish the completed manga, the server uploads the manga data to the publishing platform. At this time, users can insert advertisements to generate revenue. After publishing, users can check their revenue data on a dedicated dashboard.

[0112] As a specific example, User A inputs a story called "An adventure in which a boy defeats enemies with magical powers," and the generative AI model automatically generates a manga. User A then corrects the characters' lines and adds and inserts new backgrounds. The manga is then translated into English and published in multiple languages. User A checks the revenue generated from the published manga on the dashboard and receives the revenue. Another example of a prompt provided to the generative AI model is "Please describe a scene from an adventure story in which a boy defeats enemies with magical powers."

[0113] As described above, this system allows users to easily create high-quality manga, publish it in multiple languages, and earn revenue.

[0114] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0115] Step 1: Enter your story text

[0116] Users access the system's story input module using their own devices (PCs, smartphones, etc.). The interface has an input area where users can enter stories or scenarios in text format. For example, they can enter story text such as "A boy goes on an adventure to defeat his enemies with the power of magic."

[0117] Specific behavior:

[0118] The user enters the story text into the text area.

[0119] Click the "Send" button.

[0120] Input: Story text

[0121] Output: Story text data sent

[0122] Step 2: Sending and parsing text

[0123] The server receives the story text entered by the user and sends the data to a generative AI model, which uses natural language processing (NLP) techniques to analyze the text and extract important information, such as dividing it into scenes and identifying the events and characters that correspond to each scene.

[0124] Specific behavior:

[0125] The server receives the text data through the Web API.

[0126] Calls the NLP analysis engine to perform tokenization and scene segmentation.

[0127] Input: Text data

[0128] Output: Analyzed text data (data split by scene)

[0129] Step 3: Auto-generate the manga

[0130] Based on the analyzed story text, the server uses a generative AI model to automatically generate each page of the manga, including character designs, backgrounds, and text box placement. Corresponding illustrations and characters are generated and integrated based on each scene.

[0131] Specific behavior:

[0132] The server sends the prompt text and analysis data to the generative AI model.

[0133] The AI ​​model generates corresponding images and text data for each scene and composes the page according to the format.

[0134] Input: Analyzed text data, prompt statement

[0135] Output: Automatically generated manga page data

[0136] Step 4: Corrections and additional editing

[0137] The generated manga page is displayed to the user from the server. The user can check the displayed manga and make changes to the dialogue or add backgrounds as needed. Editing can be done easily with drag-and-drop and click operations. Once the changes are complete, the data is sent back to the server.

[0138] Specific behavior:

[0139] The user makes modifications using the editing interface (e.g., click on a text box to edit the dialogue, drag and drop an image to change its position).

[0140] Click the "Save" button to send the changes to the server.

[0141] Input: Automatically generated manga page data, user editing instructions

[0142] Output: Manga data with corrections and additions reflected

[0143] Step 5: Translation process

[0144] If a user wishes to publish in multiple languages, the server calls the translation module and translates the manga into the specified language. An AI-based translation engine is used to convert the text of the manga into other languages. The translation results are then re-incorporated into each page of the manga.

[0145] Specific behavior:

[0146] The user selects the desired language and clicks the "Translate" button.

[0147] The server calls the translation engine to translate the text and incorporates the translated text into the comic page.

[0148] Input: Manga data with corrections and additions reflected, user's language selection

[0149] Output: Manga data translated into multiple languages

[0150] Step 6: Publish and monetize your manga

[0151] When a user indicates their intention to publish a manga, the server uploads the manga data to the publishing platform. When publishing, advertisements are inserted into each page of the manga, and a mechanism for tracking revenue is included. After publishing, users can check revenue data on a dedicated dashboard.

[0152] Specific behavior:

[0153] The user clicks the Publish button.

[0154] The server accesses the public platform's API and uploads the manga data.

[0155] An ad insertion engine places ads on pages and collects revenue data.

[0156] Revenue data is displayed in the user dashboard.

[0157] Input: Manga data translated into multiple languages, publishing instructions

[0158] Output: Published manga data and revenue data

[0159] The above is a detailed flow of each processing step of this system.

[0160] (Application example 1)

[0161] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0162] Traditional manga production has been extremely difficult for users without specialized skills, and there have been issues with publishing in multiple languages ​​and monetizing the work being difficult. In addition, new production and publishing methods using smartphones and head-mounted displays have not yet been established, creating a high barrier to entry for users. There is a need to solve these issues and provide a system that allows many users to easily create, publish, and monetize manga.

[0163] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0164] In this invention, the server includes means for inputting story text, means for automatically generating manga illustrations and characters based on the story text using a generative AI model, means for providing an interface that allows users to make corrections and additions, means for translating the generated manga into multiple languages, means for publishing the generated and corrected manga, means for supporting smartphones or head-mounted displays, and means for managing content publication and monetization, thereby enabling users to easily create high-quality manga and publish and monetize them through various devices.

[0165] "Story text" refers to text that the user inputs as character information to describe a story or scenario.

[0166] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate manga illustrations and text based on input story text.

[0167] The "interface" refers to the operation screen and operation means that allow the user to modify and add to the created comic.

[0168] "Multilingual translation" refers to the process of translating the text of a manga from one language to another.

[0169] "Publishing" means uploading the created and modified manga to an online platform or other media, making it accessible to the general public.

[0170] A "smartphone" is a type of portable multi-function communication terminal that can install and run applications.

[0171] A "head-mounted display" is a display device that provides visual information when worn on the user's head.

[0172] "Content publishing and monetization" refers to the process of publishing created and modified comics and earning revenue through advertising, etc.

[0173] This invention provides a system for easily creating and publishing manga. The system consists of a server, a terminal (a smartphone or a head-mounted display), and multiple software modules.

[0174] Story text input

[0175] A user uses a terminal to access the story input module of the system. The user interface provides a text area where the user can input their own story or scenario. Let's say the user wants to input a story about a boy's adventure of defeating enemies with magical powers into this text area.

[0176] Generative AI Models

[0177] The server receives the story text entered by the user and passes it to the generative AI model. The generative AI model uses natural language processing (NLP) technology to analyze the story text and generate illustrations and text corresponding to each scene. Character designs and backgrounds are also automatically created. As a result, each page of the manga is automatically generated.

[0178] User-modified and added interface

[0179] The generated manga is displayed to the user from the server. The user can check the displayed manga and make corrections or additions as necessary. For example, they can change the lines of the characters or replace the background. The interface is designed to allow easy editing with drag-and-drop and click operations. Once the user has completed their corrections and additions, the data is sent to the server and the updated manga data is saved.

[0180] Translation Module

[0181] If a user wishes to publish in multiple languages, the server uses a translation module to translate the manga into the specified language. This module uses an AI-based translation engine to translate the text portion of the manga into other languages. The translation results are then incorporated back into the manga, generating multilingual manga data.

[0182] Publishing and Monetizing Your Manga

[0183] Once a user has completed their manga and indicates their intention to publish it, the server uploads the manga data to the publishing platform. The platform also provides the ability to insert advertisements to generate revenue. After publishing, users can check their revenue data on a dedicated dashboard.

[0184] For example, a user can input a story such as "A boy's adventure in which he defeats enemies with magical powers," and the generative AI model will automatically generate a manga. The user can then edit the characters' lines and add additional backgrounds. The manga will then be translated into English and published in multiple languages. The user can then check the revenue generated by the published manga on their dashboard and earn income.

[0185] An example prompt uses the following format:

[0186] A boy's adventure to defeat enemies with magical powers

[0187] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0188] Step 1:

[0189] A user uses a terminal to access a story text input interface.

[0190] Input: The user types a story or scenario into a text area.

[0191] Output: The input story text data is generated.

[0192] Specific operation: The user enters the sentence "A boy's adventure to defeat enemies with the power of magic" into the text area and presses the send button.

[0193] Step 2:

[0194] The server passes the story text received from the user to the generative AI model.

[0195] Input: Story text data entered by the user.

[0196] Output: Story text data passed to the generative AI model.

[0197] Specific operation: The server sends the story text data to the natural language processing engine.

[0198] Step 3:

[0199] The generative AI model analyzes the story text and automatically generates illustrations and text corresponding to each scene.

[0200] Input: Story text data passed to the generative AI model.

[0201] Output: Automatically generated manga data.

[0202] Specific operation: The generative AI model generates character designs, backgrounds, dialogue, etc. based on the story text, and creates manga pages.

[0203] Step 4:

[0204] The server displays the generated comic to the user.

[0205] Input: Auto-generated manga data.

[0206] Output: The comic displayed on the user's device.

[0207] Specific operation: The server sends the generated comic data to the user's terminal and displays it through the interface.

[0208] Step 5:

[0209] The user checks the manga and makes corrections or additions as necessary.

[0210] Input: Comic data displayed to the user.

[0211] Output: Manga data modified and added by the user.

[0212] Specific operation: The user makes modifications such as changing dialogue or adding background through the interface, using drag-and-drop and click operations.

[0213] Step 6:

[0214] The server receives the data modified and added by the user and stores the final comic data.

[0215] Input: Manga data modified and added by users.

[0216] Output: The final saved comic data.

[0217] Specific operation: The server saves the final manga data in the database.

[0218] Step 7:

[0219] If the user desires multilingual publication, the server uses a translation module to translate the manga into the specified language.

[0220] Input: Final manga data, specified language.

[0221] Output: Translated manga data.

[0222] Specific operation: The server uses an AI translation engine to translate the text of the manga and incorporates the translation results into the original manga.

[0223] Step 8:

[0224] When a user indicates their intention to publish the manga, the server uploads the manga data to the publishing platform.

[0225] Input: Final manga data.

[0226] Output: Published manga data.

[0227] Specific operation: The server accesses the publishing platform and uploads the comic data, while simultaneously inserting advertisements.

[0228] Step 9:

[0229] Users can view revenue data on a dedicated dashboard.

[0230] Input: Revenue data.

[0231] Output: Revenue data displayed on a dashboard.

[0232] What it does: Users access a dedicated dashboard where they can check their earnings status.

[0233] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0234] This invention is a system that enables users who cannot draw to easily create and publish manga, and is combined with an emotion engine. The system is composed of the following main components: a means for inputting story text, a means for automatically generating manga using a generative AI model, an interface for user corrections and additions, a means for translating into multiple languages, a means for publishing the generated and modified manga, and an emotion engine that recognizes the user's emotions.

[0235] Story text input

[0236] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs the story text into the text area. For example, the user inputs a story such as "A boy goes on an adventure to defeat his enemies with magical powers."

[0237] Utilizing the Emotion Engine

[0238] Immediately after the story text is sent, the server launches the emotion engine, which analyzes the user's facial expressions and voice data in real time. The emotion engine recognizes emotions such as smile, surprise, and anger. This information is then used in the generative AI model and in the interface for corrections and additions.

[0239] Generative AI Models

[0240] The server inputs the input story text and emotion engine data into a generation AI model, which then analyzes the story. Using natural language processing technology, the story is divided into scenes, and character designs, backgrounds, and dialogue are generated while adjusting them based on the user's emotions. For example, illustrations with brighter tones are generated for users who smile a lot.

[0241] User-modified and added interface

[0242] The generated manga is displayed to the user from the server. The user can review the displayed manga and make corrections or additions as necessary. At this time, expressions and lines for the manga characters may be automatically suggested based on the emotional data obtained by the emotion engine. The user can make final corrections using this interface, which allows for easy editing with drag-and-drop and click operations.

[0243] Translation Module

[0244] If a user wishes to publish in multiple languages, the server uses a translation module to translate the manga into the specified language. This module uses an AI-based translation engine to translate the text portion of the manga into other languages. The translated content is then incorporated back into the manga, generating multilingual manga data.

[0245] Publishing and Monetizing Your Manga

[0246] When a user indicates their intention to publish the completed manga, the server uploads the manga data to the publishing platform. At this time, a function for monetization through the insertion of advertisements is also provided. After publishing, the user can check revenue data on a dedicated dashboard. For example, if User A enters a story with a smile, such as "A boy's adventure in which he defeats enemies with the power of magic," the generative AI model will automatically generate a manga with a cheerful tone that matches that story. User A then further edits and adds character lines and facial expressions, and publishes the final version in multiple languages. User A can check and receive revenue on the dashboard.

[0247] Through this series of processes, the present invention automates the manga production process, providing a system that allows anyone to easily create, publish, and monetize high-quality manga. By combining it with an emotion engine, it is possible to generate even more appealing content that is in line with the user's emotions.

[0248] The processing flow will be explained below.

[0249] Step 1:

[0250] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs the story text into the text area. For example, the user inputs a story such as "A boy goes on an adventure to defeat his enemies with magical powers."

[0251] Step 2:

[0252] The device sends the story text entered by the user to the server. When the send button is pressed, the data is transferred using JavaScript or Ajax.

[0253] Step 3:

[0254] The server receives the story text and stores it in a database in an appropriate format, preparing it for input to the generative AI model.

[0255] Step 4:

[0256] The server starts the emotion engine immediately after sending the story text and collects the user's facial expressions and voice data in real time from the device. The emotion engine recognizes the user's emotions, such as smile, surprise, and anger.

[0257] Step 5:

[0258] The server analyzes the collected emotional data and inputs this information into the generative AI model, which is then ready to create a manga taking into account the user's emotions.

[0259] Step 6:

[0260] The server provides the story text and emotion engine data to the generative AI model, which then analyzes the story. Using natural language processing technology, the model divides the story into scenes and generates illustrations and text corresponding to each scene.

[0261] Step 7:

[0262] The generative AI model takes into account the user's emotional data to generate character designs, backgrounds, and dialogue. For example, if the user is smiling while entering a story, it will generate illustrations and dialogue with a bright tone.

[0263] Step 8:

[0264] The server receives the generated manga data (images and text corresponding to a series of scenes) and stores it in a database. At this stage, the basic pages of the manga are formed.

[0265] Step 9:

[0266] The server generates a link or view to display the generated manga data to the user and notifies the user, who can then view the generated manga on their device.

[0267] Step 10:

[0268] Users can use the provided editing interface to modify or add to the manga, for example, by changing the dialogue of characters or replacing backgrounds.

[0269] Step 11:

[0270] The editing interface also automatically suggests facial expressions and lines for characters based on the emotional data obtained by the emotion engine, which users can then modify.

[0271] Step 12:

[0272] The device sends the user's modifications and additions to the server, and after the changes are confirmed in the form or interface, the data is transferred again using JavaScript or Ajax.

[0273] Step 13:

[0274] The server receives the corrections and additional data, integrates it with the existing comic data, updates the comic data in the database, and saves the corrections.

[0275] Step 14:

[0276] The server then displays the updated manga data to the user again, allowing the user to check it with any corrections or additions reflected.

[0277] Step 15:

[0278] If the user wishes to publish in multiple languages, he or she can select the desired translation language in the interface, for example, "English."

[0279] Step 16:

[0280] The device sends a translation request to the server along with information about the selected translation language. The user's selection is communicated to the server using JavaScript or Ajax.

[0281] Step 17:

[0282] The server retrieves the manga data and inputs it into the translation module. First, it extracts the text part of the manga and passes it to the translation engine.

[0283] Step 18:

[0284] The translation module automatically translates manga text into the specified language, using an AI-based translation engine to perform language conversion.

[0285] Step 19:

[0286] The server then incorporates the translated text into the original manga data and saves it again, creating a complete manga data set in the new language.

[0287] Step 20:

[0288] The server displays the translated manga to the user, who can then view the completed multilingual manga on their device.

[0289] Step 21:

[0290] When a user indicates their intention to publish a completed manga, they press the publish button on their device, and a publish request is sent to the server.

[0291] Step 22:

[0292] The device sends a disclosure request to the server, which sends all the data required for disclosure.

[0293] Step 23:

[0294] The server receives the publishing request and uploads the manga data to the publishing platform, along with metadata such as title, summary, and tags.

[0295] Step 24:

[0296] The server performs functions to place advertisements and provide revenue data to users. It embeds advertisements in published comics and reflects revenue information on the dashboard.

[0297] Step 25:

[0298] Users can check their earnings on their device and view how much advertising revenue they are earning through a dashboard.

[0299] The above are the specific processing steps of the system that combines the emotion engine.

[0300] Example 2

[0301] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0302] Traditional manga production requires advanced skills and time, making it difficult for ordinary users to easily create high-quality manga. Furthermore, there was a lack of an automatic generation system with emotion recognition functionality, making it impossible to create content that responded to the user's emotions. Furthermore, there was a lack of automatic generation of multilingual visual representations and post-publication monetization functionality.

[0303] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0304] In this invention, the server includes: a means for a user to input a story; a means for automatically generating visual representations and text based on the story using a generative AI model; a means for providing an interface that allows the user to make corrections and additions; a means including an emotion engine that recognizes the user's emotions and reflects them in the generation process; a means for translating the generated visual representations into multiple languages; and a means for publishing the generated and modified visual representations. This makes it possible to automatically generate high-quality manga that responds to user emotions, publish them in multiple languages, and monetize them without specialized skills.

[0305] "User" refers to a general user who uses the system to input and edit stories.

[0306] A "story" is the story text that the user inputs into the system and is the basis for the visual representation.

[0307] "Generative AI model" refers to an artificial intelligence model that automatically generates visual representations and text based on a story entered by a user.

[0308] "Visual representation" refers to the graphical output, including cartoons and illustrations, automatically generated by generative AI models.

[0309] "Character" refers to text used in visual presentations, including character dialogue and explanatory text.

[0310] "Interface" refers to the screen and operating means that allow users to operate the system, and can be modified and added to.

[0311] The "emotion engine" refers to the part of the system that analyzes the user's facial expressions and voice data to recognize emotions and reflect them in the generation process.

[0312] "Multilingual translation" refers to the process of converting the generated visual and written representations into multiple different languages.

[0313] "Publishing" refers to the act of making the generated and modified visual representations available to the public online or on other platforms.

[0314] This invention is a system that enables users who cannot draw to easily create and publish manga, and is combined with an emotion engine. The system is composed of the following main components: a means for inputting story text, a means for automatically generating visual representations using a generative AI model, an interface for user corrections and additions, a means for translating into multiple languages, a means for publishing the generated and modified visual representations, and an emotion engine that recognizes the user's emotions.

[0315] Story text input

[0316] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs a story into the text area. For example, the user inputs a story such as "A boy goes on an adventure to defeat his enemies with magical powers."

[0317] Utilizing the Emotion Engine

[0318] Immediately after the story is sent, the server launches the emotion engine, which analyzes the user's facial expressions and voice data in real time. The emotion engine recognizes emotions such as smile, surprise, and anger. This information is then used in the generative AI model and in the interface for corrections and additions.

[0319] Generative AI Models

[0320] The server inputs the input story and emotion engine data into a generative AI model, which then analyzes the story. Using natural language processing technology, the story is divided into scenes, and character designs, backgrounds, and dialogue are generated while adjusting them based on the user's emotions. For example, illustrations with brighter tones are generated for users who smile a lot.

[0321] User-modified and added interface

[0322] The generated visual representation is displayed to the user from the server. The user can review the displayed visual representation and make corrections or additions as necessary. In this process, character expressions and lines may be automatically suggested based on the emotional data obtained by the emotion engine. The user can make final corrections using this interface, which allows for easy editing with drag-and-drop and click operations.

[0323] Translation Module

[0324] If the user wishes to publish in multiple languages, the server uses a translation module to translate the visual representation into the specified language. This module uses an AI-based translation engine to translate the text portion of the visual representation into other languages. The translated content is then re-integrated to generate multilingual visual representation data.

[0325] Publishing and Monetization

[0326] When a user indicates their intention to publish the completed visual representation, the server uploads the visual representation data to the publishing platform. A monetization function is also provided for this purpose. After publishing, users can check revenue data on a dedicated dashboard. For example, if User A enters a story with a smile, such as "A boy's adventure defeats enemies with magical powers," the generative AI model automatically generates a corresponding bright-toned visual representation. User A then further edits and adds character lines and facial expressions, and publishes the final version in multiple languages. User A can check and collect revenue on the dashboard.

[0327] Examples of prompt statements

[0328] "Please create a light-hearted manga about the adventures of a hero who slays a dragon. Emphasize the joy on the hero's face."

[0329] Through this series of processes, the present invention automates the manga production process, providing a system that allows anyone to easily create, publish, and monetize high-quality visual expressions. By combining it with an emotion engine, it is possible to generate even more appealing content that is in line with the user's emotions.

[0330] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0331] Step 1:

[0332] Story Input

[0333] The user uses a terminal (PC, smartphone, etc.) to access the story input module of the system and input a story. The user enters specific story text into the text area, such as "An adventure in which a boy defeats enemies with the power of magic."

[0334] Input: Story text (e.g. "A boy's adventure in defeating his enemies with magical powers")

[0335] Output: The input story text is sent to the server.

[0336] Specific operations: Open a browser on your device, log in to the system webpage, open the story input module, enter the story in the text area, and click the "Submit" button.

[0337] Step 2:

[0338] Emotional Data Analysis

[0339] The server starts the emotion engine the moment the user submits the story text. The server acquires the user's facial expressions and voice data in real time and analyzes them with the emotion engine.

[0340] Input: User's live camera video and audio data

[0341] Output: Real-time emotion data such as smile, surprise, anger, etc.

[0342] Specific operation: When the server receives the request, it requests permission to access the local camera and microphone device. With the user's permission, it acquires camera footage and audio, and analyzes them using the emotion engine.

[0343] Step 3:

[0344] Automatic manga generation

[0345] The server inputs the input story text and emotion data into a generative AI model to automatically generate a manga. Natural language processing technology is used to divide the story into scenes, and character designs, backgrounds, and dialogue are adjusted according to the user's emotions.

[0346] Input: Story text, emotion data

[0347] Output: Story divided into scenes, generated manga (characters, background, dialogue)

[0348] How it works: The server breaks down the story into scenes, sends them to the AI ​​model, and generates characters and scenes with a brighter tone, including a "smile" prompt, if there is a lot of smiling data.

[0349] Step 4:

[0350] User modifications and additions

[0351] The generated manga is displayed on the user's device from the server. The user can review the displayed manga and modify or add character designs and dialogue. Automatic suggestions are also made based on data from the emotion engine.

[0352] Input: Generated cartoon, emotion data

[0353] Output: Modified cartoon

[0354] Specific operation: The generated manga is displayed on the device, and the user enters editing mode and can change the character design, background, and dialogue using drag-and-drop and click operations.

[0355] Step 5:

[0356] Translation Processing

[0357] If the user desires multilingual publication, the server uses a translation module to translate the visual representation into the specified languages.

[0358] Input: The user's preferred language and visual representation

[0359] Output: Translated visual representation (multilingual)

[0360] What it does: The server passes the text of the manga to an AI-based translation engine, for example, to translate the Japanese manga into English and Chinese, and then re-incorporates the translated text.

[0361] Step 6:

[0362] Publishing and Monetization

[0363] Once the user has decided to publish the completed visual representation, the server uploads the visual representation data to the publishing platform. If necessary, advertisements can be inserted to generate revenue. The user can view revenue data on the dashboard.

[0364] Input: Finished visual representation, monetization request

[0365] Output: Published visual representation, revenue data

[0366] What it does: The server uploads the visual representation to the publishing platform and inserts the necessary ads. Users can view revenue data on the dashboard and understand their revenue status.

[0367] (Application example 2)

[0368] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0369] In recent years, there has been a growing demand in the field of content creation for systems that allow users who are not skilled at drawing to easily create, publish, and monetize high-quality manga. However, conventional systems have had issues with automatically generating content that reflects the user's emotions, and publishing and monetizing content in multiple languages ​​is complicated.

[0370] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting story text, a means for automatically generating illustrations and characters for a manga based on the story text using a generative AI model, an emotion recognition means for analyzing the user's emotions, and a means for adaptively adjusting the generated manga based on the emotion recognition results. This makes it possible to easily generate high-quality content that is in line with the user's emotions, and to publish and monetize it in multiple languages.

[0371] The "story text input means" is an interface device that allows the user to input the text of the story.

[0372] A "generative AI model" is an artificial intelligence algorithm that automatically generates manga illustrations and characters based on input text.

[0373] The "emotion recognition means" is a device that analyzes the user's facial expressions and voice data and recognizes the user's emotional state in real time.

[0374] The "adaptive adjustment means" is a mechanism that dynamically adjusts the generated content based on the user's emotion data obtained by the emotion recognition means.

[0375] The "modification and addition interface" is an operation panel that allows the user to modify and add to the automatically generated comic.

[0376] The "multilingual translation means" is a system that translates automatically generated manga into different specified languages.

[0377] "Publication means" is a platform for publicly disclosing the created and modified manga.

[0378] The "storage and management means" refers to a storage device and management system for permanently storing and managing the generated manga data.

[0379] The "revenue data providing means" is a function that places advertisements and provides generated revenue data to users in real time.

[0380] This invention relates to a system that enables users who are not skilled in drawing to easily create, publish, and monetize manga. This system incorporates emotion recognition means, generates high-quality content that reflects the user's emotions, and supports multilingual publishing and monetization.

[0381] 1. Story text input method

[0382] A user uses a device such as a smartphone or tablet to access a dedicated application and input story text. For example, a user can input a story called "Adventures at a Magic School." This story text is accepted by the system's story text input module.

[0383] 2. Emotion recognition means

[0384] When the server receives the input story text, it uses the device's camera and microphone to analyze the user's facial expressions and voice in real time. Specifically, it uses a facial expression recognition library (e.g., OpenCV) and voice analysis tools to identify the user's emotional state. This emotional data plays an important role in the subsequent manga generation by the generative AI model.

[0385] 3. Generative AI Models

[0386] The server automatically generates manga using a generative AI model (e.g., Stable Diffusion, GPT-3) based on the collected story text and emotion data. This AI model uses natural language processing technology to divide the story text into scenes and adjust the character design, background, and dialogue as it generates them. For example, if the user is smiling, the system generates an illustration with a bright tone.

[0387] 4. Adaptive Adjustment Measures

[0388] The generated manga is sent from the server to the user's device, where the user can review and edit it. As the user makes edits, the system automatically suggests character expressions and lines based on emotion recognition data. The interface allows for intuitive and easy editing using drag-and-drop and click operations.

[0389] 5. Multilingual Translation Tools

[0390] If a user wishes to publish in multiple languages, the server uses a translation engine (e.g., Google Translate, DeepL) to translate the text of the manga into other languages. The translated content is then re-incorporated into the manga, generating multilingual manga data.

[0391] 6. Disclosure Methods

[0392] Users can upload their completed manga to a publishing platform. The system will then publish the manga data and monetize it by inserting advertisements. This revenue data can be viewed in real time on a user-specific dashboard.

[0393] 7. Storage and management measures

[0394] The system stores the generated manga data on a cloud server and manages it permanently, allowing users to access, reuse, and re-edit their past works at any time.

[0395] Prompt Sentence Examples

[0396] Here are some examples of prompts you can enter into a generative AI model:

[0397] The user entered the story text: "Magic School Adventures".

[0398] The emotion engine identified that the user was laughing happily.

[0399] Generate a cartoon scene based on the following criteria:

[0400] Character: A cheerful and energetic student

[0401] Background: Magical school classroom

[0402] Overall tone: bright and fun

[0403] Dialogue: Lines spoken by characters in a fun way

[0404] Scene 1: "First Day at Magic School"

[0405] Scene 2: "Magic Lessons with New Friends"

[0406] Scene 3: "Amazing Magical Experiment"

[0407] In this way, this system enables anyone to easily create high-quality manga, publish it in multiple languages, and monetize it.

[0408] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0409] Step 1: Enter your story text

[0410] A user accesses the application using a device such as a smartphone or tablet. The user inputs (inputs) the text of the story into the story text input module of the application. For example, the user inputs the text "Adventures at the Magic School."

[0411] This text is sent to the backend of the system (output).

[0412] Step 2: Start Recognizing Emotions

[0413] At the same time as the story text is transmitted, the server collects the user's facial expressions and voice in real time using the device's camera and microphone (input).

[0414] The collected data is analyzed using a facial expression recognition library (e.g., OpenCV) and voice analysis tools to identify the user's emotional state (data processing).

[0415] The identified emotion data (output) is used in the next generation process.

[0416] Step 3: Generate manga using generative AI models

[0417] The server inputs the input story text and emotion data into the generative AI model (input).

[0418] Generative AI models (e.g., Stable Diffusion, GPT-3) use natural language processing techniques to divide story text into scenes and generate character designs, backgrounds, and dialogue (data calculations).

[0419] If smiling emotion data is detected, the character and background are adjusted to a brighter tone.

[0420] The generated comic data is sent to the user terminal (output).

[0421] Step 4: User Modifications and Additions

[0422] The user checks the generated manga and makes corrections or additions as necessary (input).

[0423] The system automatically suggests character expressions and lines based on emotion recognition data (data processing).

[0424] Users can easily edit using drag and drop and click operations (specific operations).

[0425] The corrected comic data is resubmitted to the server (output).

[0426] Step 5: Multilingual Translation

[0427] If the user chooses to publish in multiple languages, the server will use a translation engine (e.g., Google Translate, DeepL) to translate the text portion of the manga into the specified language (input and data processing).

[0428] The translated text is then re-incorporated into the manga data, and multilingual manga data is generated (output).

[0429] Step 6: Publish your manga

[0430] When a user indicates their intention to publish the completed manga, the server uploads the manga data to the publishing platform (input and output).

[0431] The publishing platform makes the comic data available to the public and simultaneously inserts advertisements (specific operations).

[0432] The published data can be viewed as revenue on the user's dashboard (data processing).

[0433] Step 7: Store and manage

[0434] The server stores and manages the generated manga data in cloud storage (input and output).

[0435] Users can access the saved manga data at any time and reuse or re-edit it (specific operation).

[0436] By following these steps, users can easily create high-quality, emotive comics, publish them in multiple languages, and monetize them.

[0437] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0438] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0439] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0440] [Second embodiment]

[0441] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0442] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0443] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0444] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0445] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0446] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0447] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0448] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0449] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0450] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0451] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0452] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0453] This invention is a system that allows users who cannot draw to easily create and publish manga. The system is composed of the following main components: a means for inputting story text, a means for automatically generating manga using a generative AI model, an interface for users to make corrections and additions, a means for translating the generated manga into multiple languages, and a means for publishing the generated and modified manga.

[0454] Story text input

[0455] A user accesses the story input module of the system using a terminal (PC, smartphone, etc.). The interface provides a text area where the user can input their own story or scenario. Let's say that a user wants to input a story about a boy's adventure of defeating enemies with magical powers into this text area.

[0456] Generative AI Models

[0457] The server receives the story text entered by the user and passes it to the generative AI model. The generative AI model uses natural language processing (NLP) technology to analyze the story text and generate illustrations and text corresponding to each scene. Character designs and backgrounds are also automatically created. As a result, each page of the manga is automatically generated.

[0458] User-modified and added interface

[0459] The generated manga is displayed to the user from the server. The user can check the displayed manga and make corrections or additions as necessary. For example, they can change the lines of the characters or replace the background. The interface is designed to allow easy editing with drag-and-drop and click operations. Once the user has completed their corrections and additions, the data is sent to the server and the updated manga data is saved.

[0460] Translation Module

[0461] If a user wishes to publish in multiple languages, the server uses a translation module to translate the manga into the specified language. This module uses an AI-based translation engine to translate the text portion of the manga into other languages. The translation results are then incorporated back into the manga, generating multilingual manga data.

[0462] Publishing and Monetizing Your Manga

[0463] Once a user has completed their manga and indicates their intention to publish it, the server uploads the manga data to the publishing platform. The platform also provides the ability to insert advertisements to generate revenue. After publishing, users can check their revenue data on a dedicated dashboard.

[0464] As a concrete example, User A inputs a story called "The adventure of a boy who defeats enemies with the power of magic," and the generative AI model automatically generates a manga. User A then edits the characters' lines and adds additional background. User A then translates the manga into English and publishes it in multiple languages. User A can check the revenue generated from the published manga on the dashboard and earn revenue.

[0465] In this way, the present invention automates the manga production process and provides a system that allows anyone to easily create, publish, and monetize high-quality manga.

[0466] The processing flow will be explained below.

[0467] Step 1:

[0468] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs the story text into the text area. For example, the user inputs a story titled "A boy's adventure to defeat enemies with magical powers."

[0469] Step 2:

[0470] The device sends the story text entered by the user to the server. When the send button is pressed, the data is transferred using JavaScript or Ajax.

[0471] Step 3:

[0472] The server receives the story text and stores it in a database in an appropriate format, preparing it for input to the generative AI model.

[0473] Step 4:

[0474] The server inputs the saved story text into a generative AI model, which then analyzes the story. Using natural language processing technology, the AI ​​model divides the story into scenes and generates illustrations and text corresponding to each scene.

[0475] Step 5:

[0476] The server receives the generated manga data (images and text corresponding to multiple scenes) and stores it in the database again, where a series of pages are formed as a manga.

[0477] Step 6:

[0478] The server generates links and views to display the generated manga data to the user and notifies the user. The user then views a screen on their device where they can check the generated manga.

[0479] Step 7:

[0480] Users can use the provided editing interface to modify or add to the manga, such as changing or adding character lines, backgrounds, character designs, etc.

[0481] Step 8:

[0482] The device sends the user's modifications and additions to the server, and after the changes are confirmed in the form or interface, the data is transferred again using JavaScript or Ajax.

[0483] Step 9:

[0484] The server processes the received modifications and additions and merges them with the original comic data, updating the existing comic data in the database.

[0485] Step 10:

[0486] The server then displays the updated manga data to the user again, allowing the user to check it with any corrections or additions reflected.

[0487] Step 11:

[0488] If the user wishes to publish in multiple languages, he or she can select the desired translation language in the interface, for example, "English."

[0489] Step 12:

[0490] The device sends a translation request to the server along with information about the selected translation language. The user's selection is communicated to the server using JavaScript or Ajax.

[0491] Step 13:

[0492] The server retrieves the manga data and inputs it into the translation module, which extracts the text from the manga and passes it to the translation engine.

[0493] Step 14:

[0494] The translation module automatically translates text into a specified language. It uses an AI-based translation engine to translate text.

[0495] Step 15:

[0496] The server then incorporates the translated text into the original manga and saves it again, creating manga data in the new language and saving it in the database.

[0497] Step 16:

[0498] The server displays the translated manga to the user, who can then view the translated manga on their device.

[0499] Step 17:

[0500] When a user indicates their intention to publish a completed manga, they press the publish button on their device, and a publish request is sent to the server.

[0501] Step 18:

[0502] The device sends a disclosure request to the server, and the data required for disclosure is sent.

[0503] Step 19:

[0504] The server receives the publishing request and uploads the manga data to the publishing platform, along with metadata such as title, summary, and tags.

[0505] Step 20:

[0506] The server performs functions to place advertisements and provide revenue data to users. It embeds advertisements in published comics and reflects revenue information on the dashboard.

[0507] Step 21:

[0508] Users can check their earnings on their device and view how much advertising revenue they are earning through a dashboard.

[0509] The above are the specific processing steps of the system.

[0510] Example 1

[0511] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0512] Conventional manga production methods require advanced drawing skills and time, making it difficult for users who cannot draw to easily create manga. In addition, the process of publishing manga in multiple languages ​​and monetizing them is complicated, so a system that can be easily used by general users is needed.

[0513] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0514] In this invention, the server includes an input device for inputting story text created by the user, a generation device for automatically generating illustrations and text for a manga based on the story text using a generative AI model, a display device for providing an editing interface that allows the user to make corrections and additions to the generated manga, a translation device for translating the generated manga into multiple languages, and a publishing device for publishing the generated and revised manga based on the user's specifications. This allows users to easily create high-quality manga, publish it in multiple languages, and monetize it.

[0515] An "input device" is a means by which a user inputs story text that the user has created into the system.

[0516] A "generation device" is a means for automatically generating manga illustrations and text based on story text entered by a user, using a generative AI model.

[0517] An "editing interface" is a means for providing an interface that allows a user to make corrections or additions to the generated comic.

[0518] A "display device" is a device that provides a means for a user to review and edit the generated comic.

[0519] A "translation device" is a means for translating the generated manga into multiple languages.

[0520] The "publishing device" is a means for publishing the created and modified comic book based on the user's specifications.

[0521] A "storage device" is a means for storing and managing the generated comics.

[0522] The "profit device" is a means for placing advertisements and providing users with profit data for published comics.

[0523] A "generative AI model" is an artificial intelligence model that uses natural language processing technology to analyze story text and automatically generate manga illustrations and characters.

[0524] A "prompt sentence" is an input text that instructs a generative AI model to obtain a specific output.

[0525] This invention is a system that enables users who cannot draw to easily create and publish high-quality manga. The system allows users to input story text, and a generative AI model automatically generates a manga based on that text. The system also supports the user in a series of processes to modify, add to, translate, publish, and monetize the manga.

[0526] First, a user accesses the system using their own device (PC, smartphone, etc.) and inputs story text into the story input module. For example, they input a story such as "A boy's adventure of defeating enemies with magical powers."

[0527] The server then receives the story text entered by the user and sends the data to a generative AI model, which uses natural language processing (NLP) techniques to analyze the story text and generate illustrations and characters corresponding to each scene. This automatically creates character designs and backgrounds, generating each page of the manga.

[0528] The generated manga is displayed on the user's device via the server. The user can review the displayed manga and make corrections or additions. For example, they can change the dialogue of characters or add new backgrounds. The editing interface is designed for easy use with drag-and-drop and click operations.

[0529] Furthermore, if a user wants to publish a manga in multiple languages, the server will translate the manga into the specified language using a translation module, which utilizes an AI-based translation engine to convert the text of the manga into other languages.

[0530] Finally, once the user has indicated their intention to publish the completed manga, the server uploads the manga data to the publishing platform. At this time, users can insert advertisements to generate revenue. After publishing, users can check their revenue data on a dedicated dashboard.

[0531] As a specific example, User A inputs a story called "An adventure in which a boy defeats enemies with magical powers," and the generative AI model automatically generates a manga. User A then corrects the characters' lines and adds and inserts new backgrounds. The manga is then translated into English and published in multiple languages. User A checks the revenue generated from the published manga on the dashboard and receives the revenue. Another example of a prompt provided to the generative AI model is "Please describe a scene from an adventure story in which a boy defeats enemies with magical powers."

[0532] As described above, this system allows users to easily create high-quality manga, publish it in multiple languages, and earn revenue.

[0533] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0534] Step 1: Enter your story text

[0535] Users access the system's story input module using their own devices (PCs, smartphones, etc.). The interface has an input area where users can enter stories or scenarios in text format. For example, they can enter story text such as "A boy goes on an adventure to defeat his enemies with the power of magic."

[0536] Specific behavior:

[0537] The user enters the story text into the text area.

[0538] Click the "Send" button.

[0539] Input: Story text

[0540] Output: Story text data sent

[0541] Step 2: Sending and parsing text

[0542] The server receives the story text entered by the user and sends the data to a generative AI model, which uses natural language processing (NLP) techniques to analyze the text and extract important information, such as dividing it into scenes and identifying the events and characters that correspond to each scene.

[0543] Specific behavior:

[0544] The server receives the text data through the Web API.

[0545] Calls the NLP analysis engine to perform tokenization and scene segmentation.

[0546] Input: Text data

[0547] Output: Analyzed text data (data split by scene)

[0548] Step 3: Auto-generate the manga

[0549] Based on the analyzed story text, the server uses a generative AI model to automatically generate each page of the manga, including character designs, backgrounds, and text box placement. Corresponding illustrations and characters are generated and integrated based on each scene.

[0550] Specific behavior:

[0551] The server sends the prompt text and analysis data to the generative AI model.

[0552] The AI ​​model generates corresponding images and text data for each scene and composes the page according to the format.

[0553] Input: Analyzed text data, prompt statement

[0554] Output: Automatically generated manga page data

[0555] Step 4: Corrections and additional editing

[0556] The generated manga page is displayed to the user from the server. The user can check the displayed manga and make changes to the dialogue or add backgrounds as needed. Editing can be done easily with drag-and-drop and click operations. Once the changes are complete, the data is sent back to the server.

[0557] Specific behavior:

[0558] The user makes modifications using the editing interface (e.g., click on a text box to edit the dialogue, drag and drop an image to change its position).

[0559] Click the "Save" button to send the changes to the server.

[0560] Input: Automatically generated manga page data, user editing instructions

[0561] Output: Manga data with corrections and additions reflected

[0562] Step 5: Translation process

[0563] If a user wishes to publish in multiple languages, the server calls the translation module and translates the manga into the specified language. An AI-based translation engine is used to convert the text of the manga into other languages. The translation results are then re-incorporated into each page of the manga.

[0564] Specific behavior:

[0565] The user selects the desired language and clicks the "Translate" button.

[0566] The server calls the translation engine to translate the text and incorporates the translated text into the comic page.

[0567] Input: Manga data with corrections and additions reflected, user's language selection

[0568] Output: Manga data translated into multiple languages

[0569] Step 6: Publish and monetize your manga

[0570] When a user indicates their intention to publish a manga, the server uploads the manga data to the publishing platform. When publishing, advertisements are inserted into each page of the manga, and a mechanism for tracking revenue is included. After publishing, users can check revenue data on a dedicated dashboard.

[0571] Specific behavior:

[0572] The user clicks the Publish button.

[0573] The server accesses the public platform's API and uploads the manga data.

[0574] An ad insertion engine places ads on pages and collects revenue data.

[0575] Revenue data is displayed in the user dashboard.

[0576] Input: Manga data translated into multiple languages, publishing instructions

[0577] Output: Published manga data and revenue data

[0578] The above is a detailed flow of each processing step of this system.

[0579] (Application example 1)

[0580] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0581] Traditional manga production has been extremely difficult for users without specialized skills, and there have been issues with publishing in multiple languages ​​and monetizing the work being difficult. In addition, new production and publishing methods using smartphones and head-mounted displays have not yet been established, creating a high barrier to entry for users. There is a need to solve these issues and provide a system that allows many users to easily create, publish, and monetize manga.

[0582] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0583] In this invention, the server includes means for inputting story text, means for automatically generating manga illustrations and characters based on the story text using a generative AI model, means for providing an interface that allows users to make corrections and additions, means for translating the generated manga into multiple languages, means for publishing the generated and corrected manga, means for supporting smartphones or head-mounted displays, and means for managing content publication and monetization, thereby enabling users to easily create high-quality manga and publish and monetize them through various devices.

[0584] "Story text" refers to text that the user inputs as character information to describe a story or scenario.

[0585] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate manga illustrations and text based on input story text.

[0586] The "interface" refers to the operation screen and operation means that allow the user to modify and add to the created comic.

[0587] "Multilingual translation" refers to the process of translating the text of a manga from one language to another.

[0588] "Publishing" means uploading the created and modified manga to an online platform or other media, making it accessible to the general public.

[0589] A "smartphone" is a type of portable multi-function communication terminal that can install and run applications.

[0590] A "head-mounted display" is a display device that provides visual information when worn on the user's head.

[0591] "Content publishing and monetization" refers to the process of publishing created and modified comics and earning revenue through advertising, etc.

[0592] This invention provides a system for easily creating and publishing manga. The system consists of a server, a terminal (a smartphone or a head-mounted display), and multiple software modules.

[0593] Story text input

[0594] A user uses a terminal to access the story input module of the system. The user interface provides a text area where the user can input their own story or scenario. Let's say the user wants to input a story about a boy's adventure of defeating enemies with magical powers into this text area.

[0595] Generative AI Models

[0596] The server receives the story text entered by the user and passes it to the generative AI model. The generative AI model uses natural language processing (NLP) technology to analyze the story text and generate illustrations and text corresponding to each scene. Character designs and backgrounds are also automatically created. As a result, each page of the manga is automatically generated.

[0597] User-modified and added interface

[0598] The generated manga is displayed to the user from the server. The user can check the displayed manga and make corrections or additions as necessary. For example, they can change the lines of the characters or replace the background. The interface is designed to allow easy editing with drag-and-drop and click operations. Once the user has completed their corrections and additions, the data is sent to the server and the updated manga data is saved.

[0599] Translation Module

[0600] If a user wishes to publish in multiple languages, the server uses a translation module to translate the manga into the specified language. This module uses an AI-based translation engine to translate the text portion of the manga into other languages. The translation results are then incorporated back into the manga, generating multilingual manga data.

[0601] Publishing and Monetizing Your Manga

[0602] Once a user has completed their manga and indicates their intention to publish it, the server uploads the manga data to the publishing platform. The platform also provides the ability to insert advertisements to generate revenue. After publishing, users can check their revenue data on a dedicated dashboard.

[0603] For example, a user can input a story such as "A boy's adventure in which he defeats enemies with magical powers," and the generative AI model will automatically generate a manga. The user can then edit the characters' lines and add additional backgrounds. The manga will then be translated into English and published in multiple languages. The user can then check the revenue generated by the published manga on their dashboard and earn income.

[0604] An example prompt uses the following format:

[0605] A boy's adventure to defeat enemies with magical powers

[0606] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0607] Step 1:

[0608] A user uses a terminal to access a story text input interface.

[0609] Input: The user types a story or scenario into a text area.

[0610] Output: The input story text data is generated.

[0611] Specific operation: The user enters the sentence "A boy's adventure to defeat enemies with the power of magic" into the text area and presses the send button.

[0612] Step 2:

[0613] The server passes the story text received from the user to the generative AI model.

[0614] Input: Story text data entered by the user.

[0615] Output: Story text data passed to the generative AI model.

[0616] Specific operation: The server sends the story text data to the natural language processing engine.

[0617] Step 3:

[0618] The generative AI model analyzes the story text and automatically generates illustrations and text corresponding to each scene.

[0619] Input: Story text data passed to the generative AI model.

[0620] Output: Automatically generated manga data.

[0621] Specific operation: The generative AI model generates character designs, backgrounds, dialogue, etc. based on the story text, and creates manga pages.

[0622] Step 4:

[0623] The server displays the generated comic to the user.

[0624] Input: Auto-generated manga data.

[0625] Output: The comic displayed on the user's device.

[0626] Specific operation: The server sends the generated comic data to the user's terminal and displays it through the interface.

[0627] Step 5:

[0628] The user checks the manga and makes corrections or additions as necessary.

[0629] Input: Comic data displayed to the user.

[0630] Output: Manga data modified and added by the user.

[0631] Specific operation: The user makes modifications such as changing dialogue or adding background through the interface, using drag-and-drop and click operations.

[0632] Step 6:

[0633] The server receives the data modified and added by the user and stores the final comic data.

[0634] Input: Manga data modified and added by users.

[0635] Output: The final saved comic data.

[0636] Specific operation: The server saves the final manga data in the database.

[0637] Step 7:

[0638] If the user desires multilingual publication, the server uses a translation module to translate the manga into the specified language.

[0639] Input: Final manga data, specified language.

[0640] Output: Translated manga data.

[0641] Specific operation: The server uses an AI translation engine to translate the text of the manga and incorporates the translation results into the original manga.

[0642] Step 8:

[0643] When a user indicates their intention to publish the manga, the server uploads the manga data to the publishing platform.

[0644] Input: Final manga data.

[0645] Output: Published manga data.

[0646] Specific operation: The server accesses the publishing platform and uploads the comic data, while simultaneously inserting advertisements.

[0647] Step 9:

[0648] Users can view revenue data on a dedicated dashboard.

[0649] Input: Revenue data.

[0650] Output: Revenue data displayed on a dashboard.

[0651] What it does: Users access a dedicated dashboard where they can check their earnings status.

[0652] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0653] This invention is a system that enables users who cannot draw to easily create and publish manga, and is combined with an emotion engine. The system is composed of the following main components: a means for inputting story text, a means for automatically generating manga using a generative AI model, an interface for user corrections and additions, a means for translating into multiple languages, a means for publishing the generated and modified manga, and an emotion engine that recognizes the user's emotions.

[0654] Story text input

[0655] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs the story text into the text area. For example, the user inputs a story such as "A boy goes on an adventure to defeat his enemies with magical powers."

[0656] Utilizing the Emotion Engine

[0657] Immediately after the story text is sent, the server launches the emotion engine, which analyzes the user's facial expressions and voice data in real time. The emotion engine recognizes emotions such as smile, surprise, and anger. This information is then used in the generative AI model and in the interface for corrections and additions.

[0658] Generative AI Models

[0659] The server inputs the input story text and emotion engine data into a generation AI model, which then analyzes the story. Using natural language processing technology, the story is divided into scenes, and character designs, backgrounds, and dialogue are generated while adjusting them based on the user's emotions. For example, illustrations with brighter tones are generated for users who smile a lot.

[0660] User-modified and added interface

[0661] The generated manga is displayed to the user from the server. The user can review the displayed manga and make corrections or additions as necessary. At this time, expressions and lines for the manga characters may be automatically suggested based on the emotional data obtained by the emotion engine. The user can make final corrections using this interface, which allows for easy editing with drag-and-drop and click operations.

[0662] Translation Module

[0663] If a user wishes to publish in multiple languages, the server uses a translation module to translate the manga into the specified language. This module uses an AI-based translation engine to translate the text portion of the manga into other languages. The translated content is then incorporated back into the manga, generating multilingual manga data.

[0664] Publishing and Monetizing Your Manga

[0665] When a user indicates their intention to publish the completed manga, the server uploads the manga data to the publishing platform. At this time, a function for monetization through the insertion of advertisements is also provided. After publishing, the user can check revenue data on a dedicated dashboard. For example, if User A enters a story with a smile, such as "A boy's adventure in which he defeats enemies with the power of magic," the generative AI model will automatically generate a manga with a cheerful tone that matches that story. User A then further edits and adds character lines and facial expressions, and publishes the final version in multiple languages. User A can check and receive revenue on the dashboard.

[0666] Through this series of processes, the present invention automates the manga production process, providing a system that allows anyone to easily create, publish, and monetize high-quality manga. By combining it with an emotion engine, it is possible to generate even more appealing content that is in line with the user's emotions.

[0667] The processing flow will be explained below.

[0668] Step 1:

[0669] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs the story text into the text area. For example, the user inputs a story such as "A boy goes on an adventure to defeat his enemies with magical powers."

[0670] Step 2:

[0671] The device sends the story text entered by the user to the server. When the send button is pressed, the data is transferred using JavaScript or Ajax.

[0672] Step 3:

[0673] The server receives the story text and stores it in a database in an appropriate format, preparing it for input to the generative AI model.

[0674] Step 4:

[0675] The server starts the emotion engine immediately after sending the story text and collects the user's facial expressions and voice data in real time from the device. The emotion engine recognizes the user's emotions, such as smile, surprise, and anger.

[0676] Step 5:

[0677] The server analyzes the collected emotional data and inputs this information into the generative AI model, which is then ready to create a manga taking into account the user's emotions.

[0678] Step 6:

[0679] The server provides the story text and emotion engine data to the generative AI model, which then analyzes the story. Using natural language processing technology, the model divides the story into scenes and generates illustrations and text corresponding to each scene.

[0680] Step 7:

[0681] The generative AI model takes into account the user's emotional data to generate character designs, backgrounds, and dialogue. For example, if the user is smiling while entering a story, it will generate illustrations and dialogue with a bright tone.

[0682] Step 8:

[0683] The server receives the generated manga data (images and text corresponding to a series of scenes) and stores it in a database. At this stage, the basic pages of the manga are formed.

[0684] Step 9:

[0685] The server generates a link or view to display the generated manga data to the user and notifies the user, who can then view the generated manga on their device.

[0686] Step 10:

[0687] Users can use the provided editing interface to modify or add to the manga, for example, by changing the dialogue of characters or replacing backgrounds.

[0688] Step 11:

[0689] The editing interface also automatically suggests facial expressions and lines for characters based on the emotional data obtained by the emotion engine, which users can then modify.

[0690] Step 12:

[0691] The device sends the user's modifications and additions to the server, and after the changes are confirmed in the form or interface, the data is transferred again using JavaScript or Ajax.

[0692] Step 13:

[0693] The server receives the corrections and additional data, integrates it with the existing comic data, updates the comic data in the database, and saves the corrections.

[0694] Step 14:

[0695] The server then displays the updated manga data to the user again, allowing the user to check it with any corrections or additions reflected.

[0696] Step 15:

[0697] If the user wishes to publish in multiple languages, he or she can select the desired translation language in the interface, for example, "English."

[0698] Step 16:

[0699] The device sends a translation request to the server along with information about the selected translation language. The user's selection is communicated to the server using JavaScript or Ajax.

[0700] Step 17:

[0701] The server retrieves the manga data and inputs it into the translation module. First, it extracts the text part of the manga and passes it to the translation engine.

[0702] Step 18:

[0703] The translation module automatically translates manga text into the specified language, using an AI-based translation engine to perform language conversion.

[0704] Step 19:

[0705] The server then incorporates the translated text into the original manga data and saves it again, creating a complete manga data set in the new language.

[0706] Step 20:

[0707] The server displays the translated manga to the user, who can then view the completed multilingual manga on their device.

[0708] Step 21:

[0709] When a user indicates their intention to publish a completed manga, they press the publish button on their device, and a publish request is sent to the server.

[0710] Step 22:

[0711] The device sends a disclosure request to the server, which sends all the data required for disclosure.

[0712] Step 23:

[0713] The server receives the publishing request and uploads the manga data to the publishing platform, along with metadata such as title, summary, and tags.

[0714] Step 24:

[0715] The server performs functions to place advertisements and provide revenue data to users. It embeds advertisements in published comics and reflects revenue information on the dashboard.

[0716] Step 25:

[0717] Users can check their earnings on their device and view how much advertising revenue they are earning through a dashboard.

[0718] The above are the specific processing steps of the system that combines the emotion engine.

[0719] Example 2

[0720] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0721] Traditional manga production requires advanced skills and time, making it difficult for ordinary users to easily create high-quality manga. Furthermore, there was a lack of an automatic generation system with emotion recognition functionality, making it impossible to create content that responded to the user's emotions. Furthermore, there was a lack of automatic generation of multilingual visual representations and post-publication monetization functionality.

[0722] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0723] In this invention, the server includes: a means for a user to input a story; a means for automatically generating visual representations and text based on the story using a generative AI model; a means for providing an interface that allows the user to make corrections and additions; a means including an emotion engine that recognizes the user's emotions and reflects them in the generation process; a means for translating the generated visual representations into multiple languages; and a means for publishing the generated and modified visual representations. This makes it possible to automatically generate high-quality manga that responds to user emotions, publish them in multiple languages, and monetize them without specialized skills.

[0724] "User" refers to a general user who uses the system to input and edit stories.

[0725] A "story" is the story text that the user inputs into the system and is the basis for the visual representation.

[0726] "Generative AI model" refers to an artificial intelligence model that automatically generates visual representations and text based on a story entered by a user.

[0727] "Visual representation" refers to the graphical output, including cartoons and illustrations, automatically generated by generative AI models.

[0728] "Character" refers to text used in visual presentations, including character dialogue and explanatory text.

[0729] "Interface" refers to the screen and operating means that allow users to operate the system, and can be modified and added to.

[0730] The "emotion engine" refers to the part of the system that analyzes the user's facial expressions and voice data to recognize emotions and reflect them in the generation process.

[0731] "Multilingual translation" refers to the process of converting the generated visual and written representations into multiple different languages.

[0732] "Publishing" refers to the act of making the generated and modified visual representations available to the public online or on other platforms.

[0733] This invention is a system that enables users who cannot draw to easily create and publish manga, and is combined with an emotion engine. The system is composed of the following main components: a means for inputting story text, a means for automatically generating visual representations using a generative AI model, an interface for user corrections and additions, a means for translating into multiple languages, a means for publishing the generated and modified visual representations, and an emotion engine that recognizes the user's emotions.

[0734] Story text input

[0735] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs a story into the text area. For example, the user inputs a story such as "A boy goes on an adventure to defeat his enemies with magical powers."

[0736] Utilizing the Emotion Engine

[0737] Immediately after the story is sent, the server launches the emotion engine, which analyzes the user's facial expressions and voice data in real time. The emotion engine recognizes emotions such as smile, surprise, and anger. This information is then used in the generative AI model and in the interface for corrections and additions.

[0738] Generative AI Models

[0739] The server inputs the input story and emotion engine data into a generative AI model, which then analyzes the story. Using natural language processing technology, the story is divided into scenes, and character designs, backgrounds, and dialogue are generated while adjusting them based on the user's emotions. For example, illustrations with brighter tones are generated for users who smile a lot.

[0740] User-modified and added interface

[0741] The generated visual representation is displayed to the user from the server. The user can review the displayed visual representation and make corrections or additions as necessary. In this process, character expressions and lines may be automatically suggested based on the emotional data obtained by the emotion engine. The user can make final corrections using this interface, which allows for easy editing with drag-and-drop and click operations.

[0742] Translation Module

[0743] If the user wishes to publish in multiple languages, the server uses a translation module to translate the visual representation into the specified language. This module uses an AI-based translation engine to translate the text portion of the visual representation into other languages. The translated content is then re-integrated to generate multilingual visual representation data.

[0744] Publishing and Monetization

[0745] When a user indicates their intention to publish the completed visual representation, the server uploads the visual representation data to the publishing platform. A monetization function is also provided for this purpose. After publishing, users can check revenue data on a dedicated dashboard. For example, if User A enters a story with a smile, such as "A boy's adventure defeats enemies with magical powers," the generative AI model automatically generates a corresponding bright-toned visual representation. User A then further edits and adds character lines and facial expressions, and publishes the final version in multiple languages. User A can check and collect revenue on the dashboard.

[0746] Examples of prompt statements

[0747] "Please create a light-hearted manga about the adventures of a hero who slays a dragon. Emphasize the joy on the hero's face."

[0748] Through this series of processes, the present invention automates the manga production process, providing a system that allows anyone to easily create, publish, and monetize high-quality visual expressions. By combining it with an emotion engine, it is possible to generate even more appealing content that is in line with the user's emotions.

[0749] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0750] Step 1:

[0751] Story Input

[0752] The user uses a terminal (PC, smartphone, etc.) to access the story input module of the system and input a story. The user enters specific story text into the text area, such as "An adventure in which a boy defeats enemies with the power of magic."

[0753] Input: Story text (e.g. "A boy's adventure in defeating his enemies with magical powers")

[0754] Output: The input story text is sent to the server.

[0755] Specific operations: Open a browser on your device, log in to the system webpage, open the story input module, enter the story in the text area, and click the "Submit" button.

[0756] Step 2:

[0757] Emotional Data Analysis

[0758] The server starts the emotion engine the moment the user submits the story text. The server acquires the user's facial expressions and voice data in real time and analyzes them with the emotion engine.

[0759] Input: User's live camera video and audio data

[0760] Output: Real-time emotion data such as smile, surprise, anger, etc.

[0761] Specific operation: When the server receives the request, it requests permission to access the local camera and microphone device. With the user's permission, it acquires camera footage and audio, and analyzes them using the emotion engine.

[0762] Step 3:

[0763] Automatic manga generation

[0764] The server inputs the input story text and emotion data into a generative AI model to automatically generate a manga. Natural language processing technology is used to divide the story into scenes, and character designs, backgrounds, and dialogue are adjusted according to the user's emotions.

[0765] Input: Story text, emotion data

[0766] Output: Story divided into scenes, generated manga (characters, background, dialogue)

[0767] How it works: The server breaks down the story into scenes, sends them to the AI ​​model, and generates characters and scenes with a brighter tone, including a "smile" prompt, if there is a lot of smiling data.

[0768] Step 4:

[0769] User modifications and additions

[0770] The generated manga is displayed on the user's device from the server. The user can review the displayed manga and modify or add character designs and dialogue. Automatic suggestions are also made based on data from the emotion engine.

[0771] Input: Generated cartoon, emotion data

[0772] Output: Modified cartoon

[0773] Specific operation: The generated manga is displayed on the device, and the user enters editing mode and can change the character design, background, and dialogue using drag-and-drop and click operations.

[0774] Step 5:

[0775] Translation Processing

[0776] If the user desires multilingual publication, the server uses a translation module to translate the visual representation into the specified languages.

[0777] Input: The user's preferred language and visual representation

[0778] Output: Translated visual representation (multilingual)

[0779] What it does: The server passes the text of the manga to an AI-based translation engine, for example, to translate the Japanese manga into English and Chinese, and then re-incorporates the translated text.

[0780] Step 6:

[0781] Publishing and Monetization

[0782] Once the user has decided to publish the completed visual representation, the server uploads the visual representation data to the publishing platform. If necessary, advertisements can be inserted to generate revenue. The user can view revenue data on the dashboard.

[0783] Input: Finished visual representation, monetization request

[0784] Output: Published visual representation, revenue data

[0785] What it does: The server uploads the visual representation to the publishing platform and inserts the necessary ads. Users can view revenue data on the dashboard and understand their revenue status.

[0786] (Application example 2)

[0787] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0788] In recent years, there has been a growing demand in the field of content creation for systems that allow users who are not skilled at drawing to easily create, publish, and monetize high-quality manga. However, conventional systems have had issues with automatically generating content that reflects the user's emotions, and publishing and monetizing content in multiple languages ​​is complicated.

[0789] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting story text, a means for automatically generating illustrations and characters for a manga based on the story text using a generative AI model, an emotion recognition means for analyzing the user's emotions, and a means for adaptively adjusting the generated manga based on the emotion recognition results. This makes it possible to easily generate high-quality content that is in line with the user's emotions, and to publish and monetize it in multiple languages.

[0790] The "story text input means" is an interface device that allows the user to input the text of the story.

[0791] A "generative AI model" is an artificial intelligence algorithm that automatically generates manga illustrations and characters based on input text.

[0792] The "emotion recognition means" is a device that analyzes the user's facial expressions and voice data and recognizes the user's emotional state in real time.

[0793] The "adaptive adjustment means" is a mechanism that dynamically adjusts the generated content based on the user's emotion data obtained by the emotion recognition means.

[0794] The "modification and addition interface" is an operation panel that allows the user to modify and add to the automatically generated comic.

[0795] The "multilingual translation means" is a system that translates automatically generated manga into different specified languages.

[0796] "Publication means" is a platform for publicly disclosing the created and modified manga.

[0797] The "storage and management means" refers to a storage device and management system for permanently storing and managing the generated manga data.

[0798] The "revenue data providing means" is a function that places advertisements and provides generated revenue data to users in real time.

[0799] This invention relates to a system that enables users who are not skilled in drawing to easily create, publish, and monetize manga. This system incorporates emotion recognition means, generates high-quality content that reflects the user's emotions, and supports multilingual publishing and monetization.

[0800] 1. Story text input method

[0801] A user uses a device such as a smartphone or tablet to access a dedicated application and input story text. For example, a user can input a story called "Adventures at a Magic School." This story text is accepted by the system's story text input module.

[0802] 2. Emotion recognition means

[0803] When the server receives the input story text, it uses the device's camera and microphone to analyze the user's facial expressions and voice in real time. Specifically, it uses a facial expression recognition library (e.g., OpenCV) and voice analysis tools to identify the user's emotional state. This emotional data plays an important role in the subsequent manga generation by the generative AI model.

[0804] 3. Generative AI Models

[0805] The server automatically generates manga using a generative AI model (e.g., Stable Diffusion, GPT-3) based on the collected story text and emotion data. This AI model uses natural language processing technology to divide the story text into scenes and adjust the character design, background, and dialogue as it generates them. For example, if the user is smiling, the system generates an illustration with a bright tone.

[0806] 4. Adaptive Adjustment Measures

[0807] The generated manga is sent from the server to the user's device, where the user can review and edit it. As the user makes edits, the system automatically suggests character expressions and lines based on emotion recognition data. The interface allows for intuitive and easy editing using drag-and-drop and click operations.

[0808] 5. Multilingual Translation Tools

[0809] If a user wishes to publish in multiple languages, the server uses a translation engine (e.g., Google Translate, DeepL) to translate the text of the manga into other languages. The translated content is then re-incorporated into the manga, generating multilingual manga data.

[0810] 6. Disclosure Methods

[0811] Users can upload their completed manga to a publishing platform. The system will then publish the manga data and monetize it by inserting advertisements. This revenue data can be viewed in real time on a user-specific dashboard.

[0812] 7. Storage and management measures

[0813] The system stores the generated manga data on a cloud server and manages it permanently, allowing users to access, reuse, and re-edit their past works at any time.

[0814] Prompt Sentence Examples

[0815] Here are some examples of prompts you can enter into a generative AI model:

[0816] The user entered the story text: "Magic School Adventures".

[0817] The emotion engine identified that the user was laughing happily.

[0818] Generate a cartoon scene based on the following criteria:

[0819] Character: A cheerful and energetic student

[0820] Background: Magical school classroom

[0821] Overall tone: bright and fun

[0822] Dialogue: Lines spoken by characters in a fun way

[0823] Scene 1: "First Day at Magic School"

[0824] Scene 2: "Magic Lessons with New Friends"

[0825] Scene 3: "Amazing Magical Experiment"

[0826] In this way, this system enables anyone to easily create high-quality manga, publish it in multiple languages, and monetize it.

[0827] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0828] Step 1: Enter your story text

[0829] A user accesses the application using a device such as a smartphone or tablet. The user inputs (inputs) the text of the story into the story text input module of the application. For example, the user inputs the text "Adventures at the Magic School."

[0830] This text is sent to the backend of the system (output).

[0831] Step 2: Start Recognizing Emotions

[0832] At the same time as the story text is transmitted, the server collects the user's facial expressions and voice in real time using the device's camera and microphone (input).

[0833] The collected data is analyzed using a facial expression recognition library (e.g., OpenCV) and voice analysis tools to identify the user's emotional state (data processing).

[0834] The identified emotion data (output) is used in the next generation process.

[0835] Step 3: Generate manga using generative AI models

[0836] The server inputs the input story text and emotion data into the generative AI model (input).

[0837] Generative AI models (e.g., Stable Diffusion, GPT-3) use natural language processing techniques to divide story text into scenes and generate character designs, backgrounds, and dialogue (data calculations).

[0838] If smiling emotion data is detected, the character and background are adjusted to a brighter tone.

[0839] The generated comic data is sent to the user terminal (output).

[0840] Step 4: User Modifications and Additions

[0841] The user checks the generated manga and makes corrections or additions as necessary (input).

[0842] The system automatically suggests character expressions and lines based on emotion recognition data (data processing).

[0843] Users can easily edit using drag and drop and click operations (specific operations).

[0844] The corrected comic data is resubmitted to the server (output).

[0845] Step 5: Multilingual Translation

[0846] If the user chooses to publish in multiple languages, the server will use a translation engine (e.g., Google Translate, DeepL) to translate the text portion of the manga into the specified language (input and data processing).

[0847] The translated text is then re-incorporated into the manga data, and multilingual manga data is generated (output).

[0848] Step 6: Publish your manga

[0849] When a user indicates their intention to publish the completed manga, the server uploads the manga data to the publishing platform (input and output).

[0850] The publishing platform makes the comic data available to the public and simultaneously inserts advertisements (specific operations).

[0851] The published data can be viewed as revenue on the user's dashboard (data processing).

[0852] Step 7: Store and manage

[0853] The server stores and manages the generated manga data in cloud storage (input and output).

[0854] Users can access the saved manga data at any time and reuse or re-edit it (specific operation).

[0855] By following these steps, users can easily create high-quality, emotive comics, publish them in multiple languages, and monetize them.

[0856] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0857] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0858] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0859] [Third embodiment]

[0860] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0861] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0862] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0863] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0864] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0865] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0866] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0867] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0868] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0869] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0870] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0871] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0872] This invention is a system that allows users who cannot draw to easily create and publish manga. The system is composed of the following main components: a means for inputting story text, a means for automatically generating manga using a generative AI model, an interface for users to make corrections and additions, a means for translating the generated manga into multiple languages, and a means for publishing the generated and modified manga.

[0873] Story text input

[0874] A user accesses the story input module of the system using a terminal (PC, smartphone, etc.). The interface provides a text area where the user can input their own story or scenario. Let's say that a user wants to input a story about a boy's adventure of defeating enemies with magical powers into this text area.

[0875] Generative AI Models

[0876] The server receives the story text entered by the user and passes it to the generative AI model. The generative AI model uses natural language processing (NLP) technology to analyze the story text and generate illustrations and text corresponding to each scene. Character designs and backgrounds are also automatically created. As a result, each page of the manga is automatically generated.

[0877] User-modified and added interface

[0878] The generated manga is displayed to the user from the server. The user can check the displayed manga and make corrections or additions as necessary. For example, they can change the lines of the characters or replace the background. The interface is designed to allow easy editing with drag-and-drop and click operations. Once the user has completed their corrections and additions, the data is sent to the server and the updated manga data is saved.

[0879] Translation Module

[0880] If a user wishes to publish in multiple languages, the server uses a translation module to translate the manga into the specified language. This module uses an AI-based translation engine to translate the text portion of the manga into other languages. The translation results are then incorporated back into the manga, generating multilingual manga data.

[0881] Publishing and Monetizing Your Manga

[0882] Once a user has completed their manga and indicates their intention to publish it, the server uploads the manga data to the publishing platform. The platform also provides the ability to insert advertisements to generate revenue. After publishing, users can check their revenue data on a dedicated dashboard.

[0883] As a concrete example, User A inputs a story called "The adventure of a boy who defeats enemies with the power of magic," and the generative AI model automatically generates a manga. User A then edits the characters' lines and adds additional background. User A then translates the manga into English and publishes it in multiple languages. User A can check the revenue generated from the published manga on the dashboard and earn revenue.

[0884] In this way, the present invention automates the manga production process and provides a system that allows anyone to easily create, publish, and monetize high-quality manga.

[0885] The processing flow will be explained below.

[0886] Step 1:

[0887] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs the story text into the text area. For example, the user inputs a story titled "A boy's adventure to defeat enemies with magical powers."

[0888] Step 2:

[0889] The device sends the story text entered by the user to the server. When the send button is pressed, the data is transferred using JavaScript or Ajax.

[0890] Step 3:

[0891] The server receives the story text and stores it in a database in an appropriate format, preparing it for input to the generative AI model.

[0892] Step 4:

[0893] The server inputs the saved story text into a generative AI model, which then analyzes the story. Using natural language processing technology, the AI ​​model divides the story into scenes and generates illustrations and text corresponding to each scene.

[0894] Step 5:

[0895] The server receives the generated manga data (images and text corresponding to multiple scenes) and stores it in the database again, where a series of pages are formed as a manga.

[0896] Step 6:

[0897] The server generates links and views to display the generated manga data to the user and notifies the user. The user then views a screen on their device where they can check the generated manga.

[0898] Step 7:

[0899] Users can use the provided editing interface to modify or add to the manga, such as changing or adding character lines, backgrounds, character designs, etc.

[0900] Step 8:

[0901] The device sends the user's modifications and additions to the server, and after the changes are confirmed in the form or interface, the data is transferred again using JavaScript or Ajax.

[0902] Step 9:

[0903] The server processes the received modifications and additions and merges them with the original comic data, updating the existing comic data in the database.

[0904] Step 10:

[0905] The server then displays the updated manga data to the user again, allowing the user to check it with any corrections or additions reflected.

[0906] Step 11:

[0907] If the user wishes to publish in multiple languages, he or she can select the desired translation language in the interface, for example, "English."

[0908] Step 12:

[0909] The device sends a translation request to the server along with information about the selected translation language. The user's selection is communicated to the server using JavaScript or Ajax.

[0910] Step 13:

[0911] The server retrieves the manga data and inputs it into the translation module, which extracts the text from the manga and passes it to the translation engine.

[0912] Step 14:

[0913] The translation module automatically translates text into a specified language. It uses an AI-based translation engine to translate text.

[0914] Step 15:

[0915] The server then incorporates the translated text into the original manga and saves it again, creating manga data in the new language and saving it in the database.

[0916] Step 16:

[0917] The server displays the translated manga to the user, who can then view the translated manga on their device.

[0918] Step 17:

[0919] When a user indicates their intention to publish a completed manga, they press the publish button on their device, and a publish request is sent to the server.

[0920] Step 18:

[0921] The device sends a disclosure request to the server, and the data required for disclosure is sent.

[0922] Step 19:

[0923] The server receives the publishing request and uploads the manga data to the publishing platform, along with metadata such as title, summary, and tags.

[0924] Step 20:

[0925] The server performs functions to place advertisements and provide revenue data to users. It embeds advertisements in published comics and reflects revenue information on the dashboard.

[0926] Step 21:

[0927] Users can check their earnings on their device and view how much advertising revenue they are earning through a dashboard.

[0928] The above are the specific processing steps of the system.

[0929] Example 1

[0930] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0931] Conventional manga production methods require advanced drawing skills and time, making it difficult for users who cannot draw to easily create manga. In addition, the process of publishing manga in multiple languages ​​and monetizing them is complicated, so a system that can be easily used by general users is needed.

[0932] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0933] In this invention, the server includes an input device for inputting story text created by the user, a generation device for automatically generating illustrations and text for a manga based on the story text using a generative AI model, a display device for providing an editing interface that allows the user to make corrections and additions to the generated manga, a translation device for translating the generated manga into multiple languages, and a publishing device for publishing the generated and revised manga based on the user's specifications. This allows users to easily create high-quality manga, publish it in multiple languages, and monetize it.

[0934] An "input device" is a means by which a user inputs story text that the user has created into the system.

[0935] A "generation device" is a means for automatically generating manga illustrations and text based on story text entered by a user, using a generative AI model.

[0936] An "editing interface" is a means for providing an interface that allows a user to make corrections or additions to the generated comic.

[0937] A "display device" is a device that provides a means for a user to review and edit the generated comic.

[0938] A "translation device" is a means for translating the generated manga into multiple languages.

[0939] The "publishing device" is a means for publishing the created and modified comic book based on the user's specifications.

[0940] A "storage device" is a means for storing and managing the generated comics.

[0941] The "profit device" is a means for placing advertisements and providing users with profit data for published comics.

[0942] A "generative AI model" is an artificial intelligence model that uses natural language processing technology to analyze story text and automatically generate manga illustrations and characters.

[0943] A "prompt sentence" is an input text that instructs a generative AI model to obtain a specific output.

[0944] This invention is a system that enables users who cannot draw to easily create and publish high-quality manga. The system allows users to input story text, and a generative AI model automatically generates a manga based on that text. The system also supports the user in a series of processes to modify, add to, translate, publish, and monetize the manga.

[0945] First, a user accesses the system using their own device (PC, smartphone, etc.) and inputs story text into the story input module. For example, they input a story such as "A boy's adventure of defeating enemies with magical powers."

[0946] The server then receives the story text entered by the user and sends the data to a generative AI model, which uses natural language processing (NLP) techniques to analyze the story text and generate illustrations and characters corresponding to each scene. This automatically creates character designs and backgrounds, generating each page of the manga.

[0947] The generated manga is displayed on the user's device via the server. The user can review the displayed manga and make corrections or additions. For example, they can change the dialogue of characters or add new backgrounds. The editing interface is designed for easy use with drag-and-drop and click operations.

[0948] Furthermore, if a user wants to publish a manga in multiple languages, the server will translate the manga into the specified language using a translation module, which utilizes an AI-based translation engine to convert the text of the manga into other languages.

[0949] Finally, once the user has indicated their intention to publish the completed manga, the server uploads the manga data to the publishing platform. At this time, users can insert advertisements to generate revenue. After publishing, users can check their revenue data on a dedicated dashboard.

[0950] As a specific example, User A inputs a story called "An adventure in which a boy defeats enemies with magical powers," and the generative AI model automatically generates a manga. User A then corrects the characters' lines and adds and inserts new backgrounds. The manga is then translated into English and published in multiple languages. User A checks the revenue generated from the published manga on the dashboard and receives the revenue. Another example of a prompt provided to the generative AI model is "Please describe a scene from an adventure story in which a boy defeats enemies with magical powers."

[0951] As described above, this system allows users to easily create high-quality manga, publish it in multiple languages, and earn revenue.

[0952] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0953] Step 1: Enter your story text

[0954] Users access the system's story input module using their own devices (PCs, smartphones, etc.). The interface has an input area where users can enter stories or scenarios in text format. For example, they can enter story text such as "A boy goes on an adventure to defeat his enemies with the power of magic."

[0955] Specific behavior:

[0956] The user enters the story text into the text area.

[0957] Click the "Send" button.

[0958] Input: Story text

[0959] Output: Story text data sent

[0960] Step 2: Sending and parsing text

[0961] The server receives the story text entered by the user and sends the data to a generative AI model, which uses natural language processing (NLP) techniques to analyze the text and extract important information, such as dividing it into scenes and identifying the events and characters that correspond to each scene.

[0962] Specific behavior:

[0963] The server receives the text data through the Web API.

[0964] Calls the NLP analysis engine to perform tokenization and scene segmentation.

[0965] Input: Text data

[0966] Output: Analyzed text data (data split by scene)

[0967] Step 3: Auto-generate the manga

[0968] Based on the analyzed story text, the server uses a generative AI model to automatically generate each page of the manga, including character designs, backgrounds, and text box placement. Corresponding illustrations and characters are generated and integrated based on each scene.

[0969] Specific behavior:

[0970] The server sends the prompt text and analysis data to the generative AI model.

[0971] The AI ​​model generates corresponding images and text data for each scene and composes the page according to the format.

[0972] Input: Analyzed text data, prompt statement

[0973] Output: Automatically generated manga page data

[0974] Step 4: Corrections and additional editing

[0975] The generated manga page is displayed to the user from the server. The user can check the displayed manga and make changes to the dialogue or add backgrounds as needed. Editing can be done easily with drag-and-drop and click operations. Once the changes are complete, the data is sent back to the server.

[0976] Specific behavior:

[0977] The user makes modifications using the editing interface (e.g., click on a text box to edit the dialogue, drag and drop an image to change its position).

[0978] Click the "Save" button to send the changes to the server.

[0979] Input: Automatically generated manga page data, user editing instructions

[0980] Output: Manga data with corrections and additions reflected

[0981] Step 5: Translation process

[0982] If a user wishes to publish in multiple languages, the server calls the translation module and translates the manga into the specified language. An AI-based translation engine is used to convert the text of the manga into other languages. The translation results are then re-incorporated into each page of the manga.

[0983] Specific behavior:

[0984] The user selects the desired language and clicks the "Translate" button.

[0985] The server calls the translation engine to translate the text and incorporates the translated text into the comic page.

[0986] Input: Manga data with corrections and additions reflected, user's language selection

[0987] Output: Manga data translated into multiple languages

[0988] Step 6: Publish and monetize your manga

[0989] When a user indicates their intention to publish a manga, the server uploads the manga data to the publishing platform. When publishing, advertisements are inserted into each page of the manga, and a mechanism for tracking revenue is included. After publishing, users can check revenue data on a dedicated dashboard.

[0990] Specific behavior:

[0991] The user clicks the Publish button.

[0992] The server accesses the public platform's API and uploads the manga data.

[0993] An ad insertion engine places ads on pages and collects revenue data.

[0994] Revenue data is displayed in the user dashboard.

[0995] Input: Manga data translated into multiple languages, publishing instructions

[0996] Output: Published manga data and revenue data

[0997] The above is a detailed flow of each processing step of this system.

[0998] (Application example 1)

[0999] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1000] Traditional manga production has been extremely difficult for users without specialized skills, and there have been issues with publishing in multiple languages ​​and monetizing the work being difficult. In addition, new production and publishing methods using smartphones and head-mounted displays have not yet been established, creating a high barrier to entry for users. There is a need to solve these issues and provide a system that allows many users to easily create, publish, and monetize manga.

[1001] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1002] In this invention, the server includes means for inputting story text, means for automatically generating manga illustrations and characters based on the story text using a generative AI model, means for providing an interface that allows users to make corrections and additions, means for translating the generated manga into multiple languages, means for publishing the generated and corrected manga, means for supporting smartphones or head-mounted displays, and means for managing content publication and monetization, thereby enabling users to easily create high-quality manga and publish and monetize them through various devices.

[1003] "Story text" refers to text that the user inputs as character information to describe a story or scenario.

[1004] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate manga illustrations and text based on input story text.

[1005] The "interface" refers to the operation screen and operation means that allow the user to modify and add to the created comic.

[1006] "Multilingual translation" refers to the process of translating the text of a manga from one language to another.

[1007] "Publishing" means uploading the created and modified manga to an online platform or other media, making it accessible to the general public.

[1008] A "smartphone" is a type of portable multi-function communication terminal that can install and run applications.

[1009] A "head-mounted display" is a display device that provides visual information when worn on the user's head.

[1010] "Content publishing and monetization" refers to the process of publishing created and modified comics and earning revenue through advertising, etc.

[1011] This invention provides a system for easily creating and publishing manga. The system consists of a server, a terminal (a smartphone or a head-mounted display), and multiple software modules.

[1012] Story text input

[1013] A user uses a terminal to access the story input module of the system. The user interface provides a text area where the user can input their own story or scenario. Let's say the user wants to input a story about a boy's adventure of defeating enemies with magical powers into this text area.

[1014] Generative AI Models

[1015] The server receives the story text entered by the user and passes it to the generative AI model. The generative AI model uses natural language processing (NLP) technology to analyze the story text and generate illustrations and text corresponding to each scene. Character designs and backgrounds are also automatically created. As a result, each page of the manga is automatically generated.

[1016] User-modified and added interface

[1017] The generated manga is displayed to the user from the server. The user can check the displayed manga and make corrections or additions as necessary. For example, they can change the lines of the characters or replace the background. The interface is designed to allow easy editing with drag-and-drop and click operations. Once the user has completed their corrections and additions, the data is sent to the server and the updated manga data is saved.

[1018] Translation Module

[1019] If a user wishes to publish in multiple languages, the server uses a translation module to translate the manga into the specified language. This module uses an AI-based translation engine to translate the text portion of the manga into other languages. The translation results are then incorporated back into the manga, generating multilingual manga data.

[1020] Publishing and Monetizing Your Manga

[1021] Once a user has completed their manga and indicates their intention to publish it, the server uploads the manga data to the publishing platform. The platform also provides the ability to insert advertisements to generate revenue. After publishing, users can check their revenue data on a dedicated dashboard.

[1022] For example, a user can input a story such as "A boy's adventure in which he defeats enemies with magical powers," and the generative AI model will automatically generate a manga. The user can then edit the characters' lines and add additional backgrounds. The manga will then be translated into English and published in multiple languages. The user can then check the revenue generated by the published manga on their dashboard and earn income.

[1023] An example prompt uses the following format:

[1024] A boy's adventure to defeat enemies with magical powers

[1025] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1026] Step 1:

[1027] A user uses a terminal to access a story text input interface.

[1028] Input: The user types a story or scenario into a text area.

[1029] Output: The input story text data is generated.

[1030] Specific operation: The user enters the sentence "A boy's adventure to defeat enemies with the power of magic" into the text area and presses the send button.

[1031] Step 2:

[1032] The server passes the story text received from the user to the generative AI model.

[1033] Input: Story text data entered by the user.

[1034] Output: Story text data passed to the generative AI model.

[1035] Specific operation: The server sends the story text data to the natural language processing engine.

[1036] Step 3:

[1037] The generative AI model analyzes the story text and automatically generates illustrations and text corresponding to each scene.

[1038] Input: Story text data passed to the generative AI model.

[1039] Output: Automatically generated manga data.

[1040] Specific operation: The generative AI model generates character designs, backgrounds, dialogue, etc. based on the story text, and creates manga pages.

[1041] Step 4:

[1042] The server displays the generated comic to the user.

[1043] Input: Auto-generated manga data.

[1044] Output: The comic displayed on the user's device.

[1045] Specific operation: The server sends the generated comic data to the user's terminal and displays it through the interface.

[1046] Step 5:

[1047] The user checks the manga and makes corrections or additions as necessary.

[1048] Input: Comic data displayed to the user.

[1049] Output: Manga data modified and added by the user.

[1050] Specific operation: The user makes modifications such as changing dialogue or adding background through the interface, using drag-and-drop and click operations.

[1051] Step 6:

[1052] The server receives the data modified and added by the user and stores the final comic data.

[1053] Input: Manga data modified and added by users.

[1054] Output: The final saved comic data.

[1055] Specific operation: The server saves the final manga data in the database.

[1056] Step 7:

[1057] If the user desires multilingual publication, the server uses a translation module to translate the manga into the specified language.

[1058] Input: Final manga data, specified language.

[1059] Output: Translated manga data.

[1060] Specific operation: The server uses an AI translation engine to translate the text of the manga and incorporates the translation results into the original manga.

[1061] Step 8:

[1062] When a user indicates their intention to publish the manga, the server uploads the manga data to the publishing platform.

[1063] Input: Final manga data.

[1064] Output: Published manga data.

[1065] Specific operation: The server accesses the publishing platform and uploads the comic data, while simultaneously inserting advertisements.

[1066] Step 9:

[1067] Users can view revenue data on a dedicated dashboard.

[1068] Input: Revenue data.

[1069] Output: Revenue data displayed on a dashboard.

[1070] What it does: Users access a dedicated dashboard where they can check their earnings status.

[1071] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1072] This invention is a system that enables users who cannot draw to easily create and publish manga, and is combined with an emotion engine. The system is composed of the following main components: a means for inputting story text, a means for automatically generating manga using a generative AI model, an interface for user corrections and additions, a means for translating into multiple languages, a means for publishing the generated and modified manga, and an emotion engine that recognizes the user's emotions.

[1073] Story text input

[1074] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs the story text into the text area. For example, the user inputs a story such as "A boy goes on an adventure to defeat his enemies with magical powers."

[1075] Utilizing the Emotion Engine

[1076] Immediately after the story text is sent, the server launches the emotion engine, which analyzes the user's facial expressions and voice data in real time. The emotion engine recognizes emotions such as smile, surprise, and anger. This information is then used in the generative AI model and in the interface for corrections and additions.

[1077] Generative AI Models

[1078] The server inputs the input story text and emotion engine data into a generation AI model, which then analyzes the story. Using natural language processing technology, the story is divided into scenes, and character designs, backgrounds, and dialogue are generated while adjusting them based on the user's emotions. For example, illustrations with brighter tones are generated for users who smile a lot.

[1079] User-modified and added interface

[1080] The generated manga is displayed to the user from the server. The user can review the displayed manga and make corrections or additions as necessary. At this time, expressions and lines for the manga characters may be automatically suggested based on the emotional data obtained by the emotion engine. The user can make final corrections using this interface, which allows for easy editing with drag-and-drop and click operations.

[1081] Translation Module

[1082] If a user wishes to publish in multiple languages, the server uses a translation module to translate the manga into the specified language. This module uses an AI-based translation engine to translate the text portion of the manga into other languages. The translated content is then incorporated back into the manga, generating multilingual manga data.

[1083] Publishing and Monetizing Your Manga

[1084] When a user indicates their intention to publish the completed manga, the server uploads the manga data to the publishing platform. At this time, a function for monetization through the insertion of advertisements is also provided. After publishing, the user can check revenue data on a dedicated dashboard. For example, if User A enters a story with a smile, such as "A boy's adventure in which he defeats enemies with the power of magic," the generative AI model will automatically generate a manga with a cheerful tone that matches that story. User A then further edits and adds character lines and facial expressions, and publishes the final version in multiple languages. User A can check and receive revenue on the dashboard.

[1085] Through this series of processes, the present invention automates the manga production process, providing a system that allows anyone to easily create, publish, and monetize high-quality manga. By combining it with an emotion engine, it is possible to generate even more appealing content that is in line with the user's emotions.

[1086] The processing flow will be explained below.

[1087] Step 1:

[1088] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs the story text into the text area. For example, the user inputs a story such as "A boy goes on an adventure to defeat his enemies with magical powers."

[1089] Step 2:

[1090] The device sends the story text entered by the user to the server. When the send button is pressed, the data is transferred using JavaScript or Ajax.

[1091] Step 3:

[1092] The server receives the story text and stores it in a database in an appropriate format, preparing it for input to the generative AI model.

[1093] Step 4:

[1094] The server starts the emotion engine immediately after sending the story text and collects the user's facial expressions and voice data in real time from the device. The emotion engine recognizes the user's emotions, such as smile, surprise, and anger.

[1095] Step 5:

[1096] The server analyzes the collected emotional data and inputs this information into the generative AI model, which is then ready to create a manga taking into account the user's emotions.

[1097] Step 6:

[1098] The server provides the story text and emotion engine data to the generative AI model, which then analyzes the story. Using natural language processing technology, the model divides the story into scenes and generates illustrations and text corresponding to each scene.

[1099] Step 7:

[1100] The generative AI model takes into account the user's emotional data to generate character designs, backgrounds, and dialogue. For example, if the user is smiling while entering a story, it will generate illustrations and dialogue with a bright tone.

[1101] Step 8:

[1102] The server receives the generated manga data (images and text corresponding to a series of scenes) and stores it in a database. At this stage, the basic pages of the manga are formed.

[1103] Step 9:

[1104] The server generates a link or view to display the generated manga data to the user and notifies the user, who can then view the generated manga on their device.

[1105] Step 10:

[1106] Users can use the provided editing interface to modify or add to the manga, for example, by changing the dialogue of characters or replacing backgrounds.

[1107] Step 11:

[1108] The editing interface also automatically suggests facial expressions and lines for characters based on the emotional data obtained by the emotion engine, which users can then modify.

[1109] Step 12:

[1110] The device sends the user's modifications and additions to the server, and after the changes are confirmed in the form or interface, the data is transferred again using JavaScript or Ajax.

[1111] Step 13:

[1112] The server receives the corrections and additional data, integrates it with the existing comic data, updates the comic data in the database, and saves the corrections.

[1113] Step 14:

[1114] The server then displays the updated manga data to the user again, allowing the user to check it with any corrections or additions reflected.

[1115] Step 15:

[1116] If the user wishes to publish in multiple languages, he or she can select the desired translation language in the interface, for example, "English."

[1117] Step 16:

[1118] The device sends a translation request to the server along with information about the selected translation language. The user's selection is communicated to the server using JavaScript or Ajax.

[1119] Step 17:

[1120] The server retrieves the manga data and inputs it into the translation module. First, it extracts the text part of the manga and passes it to the translation engine.

[1121] Step 18:

[1122] The translation module automatically translates manga text into the specified language, using an AI-based translation engine to perform language conversion.

[1123] Step 19:

[1124] The server then incorporates the translated text into the original manga data and saves it again, creating a complete manga data set in the new language.

[1125] Step 20:

[1126] The server displays the translated manga to the user, who can then view the completed multilingual manga on their device.

[1127] Step 21:

[1128] When a user indicates their intention to publish a completed manga, they press the publish button on their device, and a publish request is sent to the server.

[1129] Step 22:

[1130] The device sends a disclosure request to the server, which sends all the data required for disclosure.

[1131] Step 23:

[1132] The server receives the publishing request and uploads the manga data to the publishing platform, along with metadata such as title, summary, and tags.

[1133] Step 24:

[1134] The server performs functions to place advertisements and provide revenue data to users. It embeds advertisements in published comics and reflects revenue information on the dashboard.

[1135] Step 25:

[1136] Users can check their earnings on their device and view how much advertising revenue they are earning through a dashboard.

[1137] The above are the specific processing steps of the system that combines the emotion engine.

[1138] Example 2

[1139] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1140] Traditional manga production requires advanced skills and time, making it difficult for ordinary users to easily create high-quality manga. Furthermore, there was a lack of an automatic generation system with emotion recognition functionality, making it impossible to create content that responded to the user's emotions. Furthermore, there was a lack of automatic generation of multilingual visual representations and post-publication monetization functionality.

[1141] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1142] In this invention, the server includes: a means for a user to input a story; a means for automatically generating visual representations and text based on the story using a generative AI model; a means for providing an interface that allows the user to make corrections and additions; a means including an emotion engine that recognizes the user's emotions and reflects them in the generation process; a means for translating the generated visual representations into multiple languages; and a means for publishing the generated and modified visual representations. This makes it possible to automatically generate high-quality manga that responds to user emotions, publish them in multiple languages, and monetize them without specialized skills.

[1143] "User" refers to a general user who uses the system to input and edit stories.

[1144] A "story" is the story text that the user inputs into the system and is the basis for the visual representation.

[1145] "Generative AI model" refers to an artificial intelligence model that automatically generates visual representations and text based on a story entered by a user.

[1146] "Visual representation" refers to the graphical output, including cartoons and illustrations, automatically generated by generative AI models.

[1147] "Character" refers to text used in visual presentations, including character dialogue and explanatory text.

[1148] "Interface" refers to the screen and operating means that allow users to operate the system, and can be modified and added to.

[1149] The "emotion engine" refers to the part of the system that analyzes the user's facial expressions and voice data to recognize emotions and reflect them in the generation process.

[1150] "Multilingual translation" refers to the process of converting the generated visual and written representations into multiple different languages.

[1151] "Publishing" refers to the act of making the generated and modified visual representations available to the public online or on other platforms.

[1152] This invention is a system that enables users who cannot draw to easily create and publish manga, and is combined with an emotion engine. The system is composed of the following main components: a means for inputting story text, a means for automatically generating visual representations using a generative AI model, an interface for user corrections and additions, a means for translating into multiple languages, a means for publishing the generated and modified visual representations, and an emotion engine that recognizes the user's emotions.

[1153] Story text input

[1154] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs a story into the text area. For example, the user inputs a story such as "A boy goes on an adventure to defeat his enemies with magical powers."

[1155] Utilizing the Emotion Engine

[1156] Immediately after the story is sent, the server launches the emotion engine, which analyzes the user's facial expressions and voice data in real time. The emotion engine recognizes emotions such as smile, surprise, and anger. This information is then used in the generative AI model and in the interface for corrections and additions.

[1157] Generative AI Models

[1158] The server inputs the input story and emotion engine data into a generative AI model, which then analyzes the story. Using natural language processing technology, the story is divided into scenes, and character designs, backgrounds, and dialogue are generated while adjusting them based on the user's emotions. For example, illustrations with brighter tones are generated for users who smile a lot.

[1159] User-modified and added interface

[1160] The generated visual representation is displayed to the user from the server. The user can review the displayed visual representation and make corrections or additions as necessary. In this process, character expressions and lines may be automatically suggested based on the emotional data obtained by the emotion engine. The user can make final corrections using this interface, which allows for easy editing with drag-and-drop and click operations.

[1161] Translation Module

[1162] If the user wishes to publish in multiple languages, the server uses a translation module to translate the visual representation into the specified language. This module uses an AI-based translation engine to translate the text portion of the visual representation into other languages. The translated content is then re-integrated to generate multilingual visual representation data.

[1163] Publishing and Monetization

[1164] When a user indicates their intention to publish the completed visual representation, the server uploads the visual representation data to the publishing platform. A monetization function is also provided for this purpose. After publishing, users can check revenue data on a dedicated dashboard. For example, if User A enters a story with a smile, such as "A boy's adventure defeats enemies with magical powers," the generative AI model automatically generates a corresponding bright-toned visual representation. User A then further edits and adds character lines and facial expressions, and publishes the final version in multiple languages. User A can check and collect revenue on the dashboard.

[1165] Examples of prompt statements

[1166] "Please create a light-hearted manga about the adventures of a hero who slays a dragon. Emphasize the joy on the hero's face."

[1167] Through this series of processes, the present invention automates the manga production process, providing a system that allows anyone to easily create, publish, and monetize high-quality visual expressions. By combining it with an emotion engine, it is possible to generate even more appealing content that is in line with the user's emotions.

[1168] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1169] Step 1:

[1170] Story Input

[1171] The user uses a terminal (PC, smartphone, etc.) to access the story input module of the system and input a story. The user enters specific story text into the text area, such as "An adventure in which a boy defeats enemies with the power of magic."

[1172] Input: Story text (e.g. "A boy's adventure in defeating his enemies with magical powers")

[1173] Output: The input story text is sent to the server.

[1174] Specific operations: Open a browser on your device, log in to the system webpage, open the story input module, enter the story in the text area, and click the "Submit" button.

[1175] Step 2:

[1176] Emotional Data Analysis

[1177] The server starts the emotion engine the moment the user submits the story text. The server acquires the user's facial expressions and voice data in real time and analyzes them with the emotion engine.

[1178] Input: User's live camera video and audio data

[1179] Output: Real-time emotion data such as smile, surprise, anger, etc.

[1180] Specific operation: When the server receives the request, it requests permission to access the local camera and microphone device. With the user's permission, it acquires camera footage and audio, and analyzes them using the emotion engine.

[1181] Step 3:

[1182] Automatic manga generation

[1183] The server inputs the input story text and emotion data into a generative AI model to automatically generate a manga. Natural language processing technology is used to divide the story into scenes, and character designs, backgrounds, and dialogue are adjusted according to the user's emotions.

[1184] Input: Story text, emotion data

[1185] Output: Story divided into scenes, generated manga (characters, background, dialogue)

[1186] How it works: The server breaks down the story into scenes, sends them to the AI ​​model, and generates characters and scenes with a brighter tone, including a "smile" prompt, if there is a lot of smiling data.

[1187] Step 4:

[1188] User modifications and additions

[1189] The generated manga is displayed on the user's device from the server. The user can review the displayed manga and modify or add character designs and dialogue. Automatic suggestions are also made based on data from the emotion engine.

[1190] Input: Generated cartoon, emotion data

[1191] Output: Modified cartoon

[1192] Specific operation: The generated manga is displayed on the device, and the user enters editing mode and can change the character design, background, and dialogue using drag-and-drop and click operations.

[1193] Step 5:

[1194] Translation Processing

[1195] If the user desires multilingual publication, the server uses a translation module to translate the visual representation into the specified languages.

[1196] Input: The user's preferred language and visual representation

[1197] Output: Translated visual representation (multilingual)

[1198] What it does: The server passes the text of the manga to an AI-based translation engine, for example, to translate the Japanese manga into English and Chinese, and then re-incorporates the translated text.

[1199] Step 6:

[1200] Publishing and Monetization

[1201] Once the user has decided to publish the completed visual representation, the server uploads the visual representation data to the publishing platform. If necessary, advertisements can be inserted to generate revenue. The user can view revenue data on the dashboard.

[1202] Input: Finished visual representation, monetization request

[1203] Output: Published visual representation, revenue data

[1204] What it does: The server uploads the visual representation to the publishing platform and inserts the necessary ads. Users can view revenue data on the dashboard and understand their revenue status.

[1205] (Application example 2)

[1206] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1207] In recent years, there has been a growing demand in the field of content creation for systems that allow users who are not skilled at drawing to easily create, publish, and monetize high-quality manga. However, conventional systems have had issues with automatically generating content that reflects the user's emotions, and publishing and monetizing content in multiple languages ​​is complicated.

[1208] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting story text, a means for automatically generating illustrations and characters for a manga based on the story text using a generative AI model, an emotion recognition means for analyzing the user's emotions, and a means for adaptively adjusting the generated manga based on the emotion recognition results. This makes it possible to easily generate high-quality content that is in line with the user's emotions, and to publish and monetize it in multiple languages.

[1209] The "story text input means" is an interface device that allows the user to input the text of the story.

[1210] A "generative AI model" is an artificial intelligence algorithm that automatically generates manga illustrations and characters based on input text.

[1211] The "emotion recognition means" is a device that analyzes the user's facial expressions and voice data and recognizes the user's emotional state in real time.

[1212] The "adaptive adjustment means" is a mechanism that dynamically adjusts the generated content based on the user's emotion data obtained by the emotion recognition means.

[1213] The "modification and addition interface" is an operation panel that allows the user to modify and add to the automatically generated comic.

[1214] The "multilingual translation means" is a system that translates automatically generated manga into different specified languages.

[1215] "Publication means" is a platform for publicly disclosing the created and modified manga.

[1216] The "storage and management means" refers to a storage device and management system for permanently storing and managing the generated manga data.

[1217] The "revenue data providing means" is a function that places advertisements and provides generated revenue data to users in real time.

[1218] This invention relates to a system that enables users who are not skilled in drawing to easily create, publish, and monetize manga. This system incorporates emotion recognition means, generates high-quality content that reflects the user's emotions, and supports multilingual publishing and monetization.

[1219] 1. Story text input method

[1220] A user uses a device such as a smartphone or tablet to access a dedicated application and input story text. For example, a user can input a story called "Adventures at a Magic School." This story text is accepted by the system's story text input module.

[1221] 2. Emotion recognition means

[1222] When the server receives the input story text, it uses the device's camera and microphone to analyze the user's facial expressions and voice in real time. Specifically, it uses a facial expression recognition library (e.g., OpenCV) and voice analysis tools to identify the user's emotional state. This emotional data plays an important role in the subsequent manga generation by the generative AI model.

[1223] 3. Generative AI Models

[1224] The server automatically generates manga using a generative AI model (e.g., Stable Diffusion, GPT-3) based on the collected story text and emotion data. This AI model uses natural language processing technology to divide the story text into scenes and adjust the character design, background, and dialogue as it generates them. For example, if the user is smiling, the system generates an illustration with a bright tone.

[1225] 4. Adaptive Adjustment Measures

[1226] The generated manga is sent from the server to the user's device, where the user can review and edit it. As the user makes edits, the system automatically suggests character expressions and lines based on emotion recognition data. The interface allows for intuitive and easy editing using drag-and-drop and click operations.

[1227] 5. Multilingual Translation Tools

[1228] If a user wishes to publish in multiple languages, the server uses a translation engine (e.g., Google Translate, DeepL) to translate the text of the manga into other languages. The translated content is then re-incorporated into the manga, generating multilingual manga data.

[1229] 6. Disclosure Methods

[1230] Users can upload their completed manga to a publishing platform. The system will then publish the manga data and monetize it by inserting advertisements. This revenue data can be viewed in real time on a user-specific dashboard.

[1231] 7. Storage and management measures

[1232] The system stores the generated manga data on a cloud server and manages it permanently, allowing users to access, reuse, and re-edit their past works at any time.

[1233] Prompt Sentence Examples

[1234] Here are some examples of prompts you can enter into a generative AI model:

[1235] The user entered the story text: "Magic School Adventures".

[1236] The emotion engine identified that the user was laughing happily.

[1237] Generate a cartoon scene based on the following criteria:

[1238] Character: A cheerful and energetic student

[1239] Background: Magical school classroom

[1240] Overall tone: bright and fun

[1241] Dialogue: Lines spoken by characters in a fun way

[1242] Scene 1: "First Day at Magic School"

[1243] Scene 2: "Magic Lessons with New Friends"

[1244] Scene 3: "Amazing Magical Experiment"

[1245] In this way, this system enables anyone to easily create high-quality manga, publish it in multiple languages, and monetize it.

[1246] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1247] Step 1: Enter your story text

[1248] A user accesses the application using a device such as a smartphone or tablet. The user inputs (inputs) the text of the story into the story text input module of the application. For example, the user inputs the text "Adventures at the Magic School."

[1249] This text is sent to the backend of the system (output).

[1250] Step 2: Start Recognizing Emotions

[1251] At the same time as the story text is transmitted, the server collects the user's facial expressions and voice in real time using the device's camera and microphone (input).

[1252] The collected data is analyzed using a facial expression recognition library (e.g., OpenCV) and voice analysis tools to identify the user's emotional state (data processing).

[1253] The identified emotion data (output) is used in the next generation process.

[1254] Step 3: Generate manga using generative AI models

[1255] The server inputs the input story text and emotion data into the generative AI model (input).

[1256] Generative AI models (e.g., Stable Diffusion, GPT-3) use natural language processing techniques to divide story text into scenes and generate character designs, backgrounds, and dialogue (data calculations).

[1257] If smiling emotion data is detected, the character and background are adjusted to a brighter tone.

[1258] The generated comic data is sent to the user terminal (output).

[1259] Step 4: User Modifications and Additions

[1260] The user checks the generated manga and makes corrections or additions as necessary (input).

[1261] The system automatically suggests character expressions and lines based on emotion recognition data (data processing).

[1262] Users can easily edit using drag and drop and click operations (specific operations).

[1263] The corrected comic data is resubmitted to the server (output).

[1264] Step 5: Multilingual Translation

[1265] If the user chooses to publish in multiple languages, the server will use a translation engine (e.g., Google Translate, DeepL) to translate the text portion of the manga into the specified language (input and data processing).

[1266] The translated text is then re-incorporated into the manga data, and multilingual manga data is generated (output).

[1267] Step 6: Publish your manga

[1268] When a user indicates their intention to publish the completed manga, the server uploads the manga data to the publishing platform (input and output).

[1269] The publishing platform makes the comic data available to the public and simultaneously inserts advertisements (specific operations).

[1270] The published data can be viewed as revenue on the user's dashboard (data processing).

[1271] Step 7: Store and manage

[1272] The server stores and manages the generated manga data in cloud storage (input and output).

[1273] Users can access the saved manga data at any time and reuse or re-edit it (specific operation).

[1274] By following these steps, users can easily create high-quality, emotive comics, publish them in multiple languages, and monetize them.

[1275] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1276] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1277] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1278] [Fourth embodiment]

[1279] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1280] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1281] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1282] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1283] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1284] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1285] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1286] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1287] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1288] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1289] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1290] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1291] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1292] This invention is a system that allows users who cannot draw to easily create and publish manga. The system is composed of the following main components: a means for inputting story text, a means for automatically generating manga using a generative AI model, an interface for users to make corrections and additions, a means for translating the generated manga into multiple languages, and a means for publishing the generated and modified manga.

[1293] Story text input

[1294] A user accesses the story input module of the system using a terminal (PC, smartphone, etc.). The interface provides a text area where the user can input their own story or scenario. Let's say that a user wants to input a story about a boy's adventure of defeating enemies with magical powers into this text area.

[1295] Generative AI Models

[1296] The server receives the story text entered by the user and passes it to the generative AI model. The generative AI model uses natural language processing (NLP) technology to analyze the story text and generate illustrations and text corresponding to each scene. Character designs and backgrounds are also automatically created. As a result, each page of the manga is automatically generated.

[1297] User-modified and added interface

[1298] The generated manga is displayed to the user from the server. The user can check the displayed manga and make corrections or additions as necessary. For example, they can change the lines of the characters or replace the background. The interface is designed to allow easy editing with drag-and-drop and click operations. Once the user has completed their corrections and additions, the data is sent to the server and the updated manga data is saved.

[1299] Translation Module

[1300] If a user wishes to publish in multiple languages, the server uses a translation module to translate the manga into the specified language. This module uses an AI-based translation engine to translate the text portion of the manga into other languages. The translation results are then incorporated back into the manga, generating multilingual manga data.

[1301] Publishing and Monetizing Your Manga

[1302] Once a user has completed their manga and indicates their intention to publish it, the server uploads the manga data to the publishing platform. The platform also provides the ability to insert advertisements to generate revenue. After publishing, users can check their revenue data on a dedicated dashboard.

[1303] As a concrete example, User A inputs a story called "The adventure of a boy who defeats enemies with the power of magic," and the generative AI model automatically generates a manga. User A then edits the characters' lines and adds additional background. User A then translates the manga into English and publishes it in multiple languages. User A can check the revenue generated from the published manga on the dashboard and earn revenue.

[1304] In this way, the present invention automates the manga production process and provides a system that allows anyone to easily create, publish, and monetize high-quality manga.

[1305] The processing flow will be explained below.

[1306] Step 1:

[1307] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs the story text into the text area. For example, the user inputs a story titled "A boy's adventure to defeat enemies with magical powers."

[1308] Step 2:

[1309] The device sends the story text entered by the user to the server. When the send button is pressed, the data is transferred using JavaScript or Ajax.

[1310] Step 3:

[1311] The server receives the story text and stores it in a database in an appropriate format, preparing it for input to the generative AI model.

[1312] Step 4:

[1313] The server inputs the saved story text into a generative AI model, which then analyzes the story. Using natural language processing technology, the AI ​​model divides the story into scenes and generates illustrations and text corresponding to each scene.

[1314] Step 5:

[1315] The server receives the generated manga data (images and text corresponding to multiple scenes) and stores it in the database again, where a series of pages are formed as a manga.

[1316] Step 6:

[1317] The server generates links and views to display the generated manga data to the user and notifies the user. The user then views a screen on their device where they can check the generated manga.

[1318] Step 7:

[1319] Users can use the provided editing interface to modify or add to the manga, such as changing or adding character lines, backgrounds, character designs, etc.

[1320] Step 8:

[1321] The device sends the user's modifications and additions to the server, and after the changes are confirmed in the form or interface, the data is transferred again using JavaScript or Ajax.

[1322] Step 9:

[1323] The server processes the received modifications and additions and merges them with the original comic data, updating the existing comic data in the database.

[1324] Step 10:

[1325] The server then displays the updated manga data to the user again, allowing the user to check it with any corrections or additions reflected.

[1326] Step 11:

[1327] If the user wishes to publish in multiple languages, he or she can select the desired translation language in the interface, for example, "English."

[1328] Step 12:

[1329] The device sends a translation request to the server along with information about the selected translation language. The user's selection is communicated to the server using JavaScript or Ajax.

[1330] Step 13:

[1331] The server retrieves the manga data and inputs it into the translation module, which extracts the text from the manga and passes it to the translation engine.

[1332] Step 14:

[1333] The translation module automatically translates text into a specified language. It uses an AI-based translation engine to translate text.

[1334] Step 15:

[1335] The server then incorporates the translated text into the original manga and saves it again, creating manga data in the new language and saving it in the database.

[1336] Step 16:

[1337] The server displays the translated manga to the user, who can then view the translated manga on their device.

[1338] Step 17:

[1339] When a user indicates their intention to publish a completed manga, they press the publish button on their device, and a publish request is sent to the server.

[1340] Step 18:

[1341] The device sends a disclosure request to the server, and the data required for disclosure is sent.

[1342] Step 19:

[1343] The server receives the publishing request and uploads the manga data to the publishing platform, along with metadata such as title, summary, and tags.

[1344] Step 20:

[1345] The server performs functions to place advertisements and provide revenue data to users. It embeds advertisements in published comics and reflects revenue information on the dashboard.

[1346] Step 21:

[1347] Users can check their earnings on their device and view how much advertising revenue they are earning through a dashboard.

[1348] The above are the specific processing steps of the system.

[1349] Example 1

[1350] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1351] Conventional manga production methods require advanced drawing skills and time, making it difficult for users who cannot draw to easily create manga. In addition, the process of publishing manga in multiple languages ​​and monetizing them is complicated, so a system that can be easily used by general users is needed.

[1352] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1353] In this invention, the server includes an input device for inputting story text created by the user, a generation device for automatically generating illustrations and text for a manga based on the story text using a generative AI model, a display device for providing an editing interface that allows the user to make corrections and additions to the generated manga, a translation device for translating the generated manga into multiple languages, and a publishing device for publishing the generated and revised manga based on the user's specifications. This allows users to easily create high-quality manga, publish it in multiple languages, and monetize it.

[1354] An "input device" is a means by which a user inputs story text that the user has created into the system.

[1355] A "generation device" is a means for automatically generating manga illustrations and text based on story text entered by a user, using a generative AI model.

[1356] An "editing interface" is a means for providing an interface that allows a user to make corrections or additions to the generated comic.

[1357] A "display device" is a device that provides a means for a user to review and edit the generated comic.

[1358] A "translation device" is a means for translating the generated manga into multiple languages.

[1359] The "publishing device" is a means for publishing the created and modified comic book based on the user's specifications.

[1360] A "storage device" is a means for storing and managing the generated comics.

[1361] The "profit device" is a means for placing advertisements and providing users with profit data for published comics.

[1362] A "generative AI model" is an artificial intelligence model that uses natural language processing technology to analyze story text and automatically generate manga illustrations and characters.

[1363] A "prompt sentence" is an input text that instructs a generative AI model to obtain a specific output.

[1364] This invention is a system that enables users who cannot draw to easily create and publish high-quality manga. The system allows users to input story text, and a generative AI model automatically generates a manga based on that text. The system also supports the user in a series of processes to modify, add to, translate, publish, and monetize the manga.

[1365] First, a user accesses the system using their own device (PC, smartphone, etc.) and inputs story text into the story input module. For example, they input a story such as "A boy's adventure of defeating enemies with magical powers."

[1366] The server then receives the story text entered by the user and sends the data to a generative AI model, which uses natural language processing (NLP) techniques to analyze the story text and generate illustrations and characters corresponding to each scene. This automatically creates character designs and backgrounds, generating each page of the manga.

[1367] The generated manga is displayed on the user's device via the server. The user can review the displayed manga and make corrections or additions. For example, they can change the dialogue of characters or add new backgrounds. The editing interface is designed for easy use with drag-and-drop and click operations.

[1368] Furthermore, if a user wants to publish a manga in multiple languages, the server will translate the manga into the specified language using a translation module, which utilizes an AI-based translation engine to convert the text of the manga into other languages.

[1369] Finally, once the user has indicated their intention to publish the completed manga, the server uploads the manga data to the publishing platform. At this time, users can insert advertisements to generate revenue. After publishing, users can check their revenue data on a dedicated dashboard.

[1370] As a specific example, User A inputs a story called "An adventure in which a boy defeats enemies with magical powers," and the generative AI model automatically generates a manga. User A then corrects the characters' lines and adds and inserts new backgrounds. The manga is then translated into English and published in multiple languages. User A checks the revenue generated from the published manga on the dashboard and receives the revenue. Another example of a prompt provided to the generative AI model is "Please describe a scene from an adventure story in which a boy defeats enemies with magical powers."

[1371] As described above, this system allows users to easily create high-quality manga, publish it in multiple languages, and earn revenue.

[1372] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1373] Step 1: Enter your story text

[1374] Users access the system's story input module using their own devices (PCs, smartphones, etc.). The interface has an input area where users can enter stories or scenarios in text format. For example, they can enter story text such as "A boy goes on an adventure to defeat his enemies with the power of magic."

[1375] Specific behavior:

[1376] The user enters the story text into the text area.

[1377] Click the "Send" button.

[1378] Input: Story text

[1379] Output: Story text data sent

[1380] Step 2: Sending and parsing text

[1381] The server receives the story text entered by the user and sends the data to a generative AI model, which uses natural language processing (NLP) techniques to analyze the text and extract important information, such as dividing it into scenes and identifying the events and characters that correspond to each scene.

[1382] Specific behavior:

[1383] The server receives the text data through the Web API.

[1384] Calls the NLP analysis engine to perform tokenization and scene segmentation.

[1385] Input: Text data

[1386] Output: Analyzed text data (data split by scene)

[1387] Step 3: Auto-generate the manga

[1388] Based on the analyzed story text, the server uses a generative AI model to automatically generate each page of the manga, including character designs, backgrounds, and text box placement. Corresponding illustrations and characters are generated and integrated based on each scene.

[1389] Specific behavior:

[1390] The server sends the prompt text and analysis data to the generative AI model.

[1391] The AI ​​model generates corresponding images and text data for each scene and composes the page according to the format.

[1392] Input: Analyzed text data, prompt statement

[1393] Output: Automatically generated manga page data

[1394] Step 4: Corrections and additional editing

[1395] The generated manga page is displayed to the user from the server. The user can check the displayed manga and make changes to the dialogue or add backgrounds as needed. Editing can be done easily with drag-and-drop and click operations. Once the changes are complete, the data is sent back to the server.

[1396] Specific behavior:

[1397] The user makes modifications using the editing interface (e.g., click on a text box to edit the dialogue, drag and drop an image to change its position).

[1398] Click the "Save" button to send the changes to the server.

[1399] Input: Automatically generated manga page data, user editing instructions

[1400] Output: Manga data with corrections and additions reflected

[1401] Step 5: Translation process

[1402] If a user wishes to publish in multiple languages, the server calls the translation module and translates the manga into the specified language. An AI-based translation engine is used to convert the text of the manga into other languages. The translation results are then re-incorporated into each page of the manga.

[1403] Specific behavior:

[1404] The user selects the desired language and clicks the "Translate" button.

[1405] The server calls the translation engine to translate the text and incorporates the translated text into the comic page.

[1406] Input: Manga data with corrections and additions reflected, user's language selection

[1407] Output: Manga data translated into multiple languages

[1408] Step 6: Publish and monetize your manga

[1409] When a user indicates their intention to publish a manga, the server uploads the manga data to the publishing platform. When publishing, advertisements are inserted into each page of the manga, and a mechanism for tracking revenue is included. After publishing, users can check revenue data on a dedicated dashboard.

[1410] Specific behavior:

[1411] The user clicks the Publish button.

[1412] The server accesses the public platform's API and uploads the manga data.

[1413] An ad insertion engine places ads on pages and collects revenue data.

[1414] Revenue data is displayed in the user dashboard.

[1415] Input: Manga data translated into multiple languages, publishing instructions

[1416] Output: Published manga data and revenue data

[1417] The above is a detailed flow of each processing step of this system.

[1418] (Application example 1)

[1419] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1420] Traditional manga production has been extremely difficult for users without specialized skills, and there have been issues with publishing in multiple languages ​​and monetizing the work being difficult. In addition, new production and publishing methods using smartphones and head-mounted displays have not yet been established, creating a high barrier to entry for users. There is a need to solve these issues and provide a system that allows many users to easily create, publish, and monetize manga.

[1421] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1422] In this invention, the server includes means for inputting story text, means for automatically generating manga illustrations and characters based on the story text using a generative AI model, means for providing an interface that allows users to make corrections and additions, means for translating the generated manga into multiple languages, means for publishing the generated and corrected manga, means for supporting smartphones or head-mounted displays, and means for managing content publication and monetization, thereby enabling users to easily create high-quality manga and publish and monetize them through various devices.

[1423] "Story text" refers to text that the user inputs as character information to describe a story or scenario.

[1424] A "generative AI model" is a model that uses artificial intelligence technology to automatically generate manga illustrations and text based on input story text.

[1425] The "interface" refers to the operation screen and operation means that allow the user to modify and add to the created comic.

[1426] "Multilingual translation" refers to the process of translating the text of a manga from one language to another.

[1427] "Publishing" means uploading the created and modified manga to an online platform or other media, making it accessible to the general public.

[1428] A "smartphone" is a type of portable multi-function communication terminal that can install and run applications.

[1429] A "head-mounted display" is a display device that provides visual information when worn on the user's head.

[1430] "Content publishing and monetization" refers to the process of publishing created and modified comics and earning revenue through advertising, etc.

[1431] This invention provides a system for easily creating and publishing manga. The system consists of a server, a terminal (a smartphone or a head-mounted display), and multiple software modules.

[1432] Story text input

[1433] A user uses a terminal to access the story input module of the system. The user interface provides a text area where the user can input their own story or scenario. Let's say the user wants to input a story about a boy's adventure of defeating enemies with magical powers into this text area.

[1434] Generative AI Models

[1435] The server receives the story text entered by the user and passes it to the generative AI model. The generative AI model uses natural language processing (NLP) technology to analyze the story text and generate illustrations and text corresponding to each scene. Character designs and backgrounds are also automatically created. As a result, each page of the manga is automatically generated.

[1436] User-modified and added interface

[1437] The generated manga is displayed to the user from the server. The user can check the displayed manga and make corrections or additions as necessary. For example, they can change the lines of the characters or replace the background. The interface is designed to allow easy editing with drag-and-drop and click operations. Once the user has completed their corrections and additions, the data is sent to the server and the updated manga data is saved.

[1438] Translation Module

[1439] If a user wishes to publish in multiple languages, the server uses a translation module to translate the manga into the specified language. This module uses an AI-based translation engine to translate the text portion of the manga into other languages. The translation results are then incorporated back into the manga, generating multilingual manga data.

[1440] Publishing and Monetizing Your Manga

[1441] Once a user has completed their manga and indicates their intention to publish it, the server uploads the manga data to the publishing platform. The platform also provides the ability to insert advertisements to generate revenue. After publishing, users can check their revenue data on a dedicated dashboard.

[1442] For example, a user can input a story such as "A boy's adventure in which he defeats enemies with magical powers," and the generative AI model will automatically generate a manga. The user can then edit the characters' lines and add additional backgrounds. The manga will then be translated into English and published in multiple languages. The user can then check the revenue generated by the published manga on their dashboard and earn income.

[1443] An example prompt uses the following format:

[1444] A boy's adventure to defeat enemies with magical powers

[1445] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1446] Step 1:

[1447] A user uses a terminal to access a story text input interface.

[1448] Input: The user types a story or scenario into a text area.

[1449] Output: The input story text data is generated.

[1450] Specific operation: The user enters the sentence "A boy's adventure to defeat enemies with the power of magic" into the text area and presses the send button.

[1451] Step 2:

[1452] The server passes the story text received from the user to the generative AI model.

[1453] Input: Story text data entered by the user.

[1454] Output: Story text data passed to the generative AI model.

[1455] Specific operation: The server sends the story text data to the natural language processing engine.

[1456] Step 3:

[1457] The generative AI model analyzes the story text and automatically generates illustrations and text corresponding to each scene.

[1458] Input: Story text data passed to the generative AI model.

[1459] Output: Automatically generated manga data.

[1460] Specific operation: The generative AI model generates character designs, backgrounds, dialogue, etc. based on the story text, and creates manga pages.

[1461] Step 4:

[1462] The server displays the generated comic to the user.

[1463] Input: Auto-generated manga data.

[1464] Output: The comic displayed on the user's device.

[1465] Specific operation: The server sends the generated comic data to the user's terminal and displays it through the interface.

[1466] Step 5:

[1467] The user checks the manga and makes corrections or additions as necessary.

[1468] Input: Comic data displayed to the user.

[1469] Output: Manga data modified and added by the user.

[1470] Specific operation: The user makes modifications such as changing dialogue or adding background through the interface, using drag-and-drop and click operations.

[1471] Step 6:

[1472] The server receives the data modified and added by the user and stores the final comic data.

[1473] Input: Manga data modified and added by users.

[1474] Output: The final saved comic data.

[1475] Specific operation: The server saves the final manga data in the database.

[1476] Step 7:

[1477] If the user desires multilingual publication, the server uses a translation module to translate the manga into the specified language.

[1478] Input: Final manga data, specified language.

[1479] Output: Translated manga data.

[1480] Specific operation: The server uses an AI translation engine to translate the text of the manga and incorporates the translation results into the original manga.

[1481] Step 8:

[1482] When a user indicates their intention to publish the manga, the server uploads the manga data to the publishing platform.

[1483] Input: Final manga data.

[1484] Output: Published manga data.

[1485] Specific operation: The server accesses the publishing platform and uploads the comic data, while simultaneously inserting advertisements.

[1486] Step 9:

[1487] Users can view revenue data on a dedicated dashboard.

[1488] Input: Revenue data.

[1489] Output: Revenue data displayed on a dashboard.

[1490] What it does: Users access a dedicated dashboard where they can check their earnings status.

[1491] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1492] This invention is a system that enables users who cannot draw to easily create and publish manga, and is combined with an emotion engine. The system is composed of the following main components: a means for inputting story text, a means for automatically generating manga using a generative AI model, an interface for user corrections and additions, a means for translating into multiple languages, a means for publishing the generated and modified manga, and an emotion engine that recognizes the user's emotions.

[1493] Story text input

[1494] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs the story text into the text area. For example, the user inputs a story such as "A boy goes on an adventure to defeat his enemies with magical powers."

[1495] Utilizing the Emotion Engine

[1496] Immediately after the story text is sent, the server launches the emotion engine, which analyzes the user's facial expressions and voice data in real time. The emotion engine recognizes emotions such as smile, surprise, and anger. This information is then used in the generative AI model and in the interface for corrections and additions.

[1497] Generative AI Models

[1498] The server inputs the input story text and emotion engine data into a generation AI model, which then analyzes the story. Using natural language processing technology, the story is divided into scenes, and character designs, backgrounds, and dialogue are generated while adjusting them based on the user's emotions. For example, illustrations with brighter tones are generated for users who smile a lot.

[1499] User-modified and added interface

[1500] The generated manga is displayed to the user from the server. The user can review the displayed manga and make corrections or additions as necessary. At this time, expressions and lines for the manga characters may be automatically suggested based on the emotional data obtained by the emotion engine. The user can make final corrections using this interface, which allows for easy editing with drag-and-drop and click operations.

[1501] Translation Module

[1502] If a user wishes to publish in multiple languages, the server uses a translation module to translate the manga into the specified language. This module uses an AI-based translation engine to translate the text portion of the manga into other languages. The translated content is then incorporated back into the manga, generating multilingual manga data.

[1503] Publishing and Monetizing Your Manga

[1504] When a user indicates their intention to publish the completed manga, the server uploads the manga data to the publishing platform. At this time, a function for monetization through the insertion of advertisements is also provided. After publishing, the user can check revenue data on a dedicated dashboard. For example, if User A enters a story with a smile, such as "A boy's adventure in which he defeats enemies with the power of magic," the generative AI model will automatically generate a manga with a cheerful tone that matches that story. User A then further edits and adds character lines and facial expressions, and publishes the final version in multiple languages. User A can check and receive revenue on the dashboard.

[1505] Through this series of processes, the present invention automates the manga production process, providing a system that allows anyone to easily create, publish, and monetize high-quality manga. By combining it with an emotion engine, it is possible to generate even more appealing content that is in line with the user's emotions.

[1506] The processing flow will be explained below.

[1507] Step 1:

[1508] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs the story text into the text area. For example, the user inputs a story such as "A boy goes on an adventure to defeat his enemies with magical powers."

[1509] Step 2:

[1510] The device sends the story text entered by the user to the server. When the send button is pressed, the data is transferred using JavaScript or Ajax.

[1511] Step 3:

[1512] The server receives the story text and stores it in a database in an appropriate format, preparing it for input to the generative AI model.

[1513] Step 4:

[1514] The server starts the emotion engine immediately after sending the story text and collects the user's facial expressions and voice data in real time from the device. The emotion engine recognizes the user's emotions, such as smile, surprise, and anger.

[1515] Step 5:

[1516] The server analyzes the collected emotional data and inputs this information into the generative AI model, which is then ready to create a manga taking into account the user's emotions.

[1517] Step 6:

[1518] The server provides the story text and emotion engine data to the generative AI model, which then analyzes the story. Using natural language processing technology, the model divides the story into scenes and generates illustrations and text corresponding to each scene.

[1519] Step 7:

[1520] The generative AI model takes into account the user's emotional data to generate character designs, backgrounds, and dialogue. For example, if the user is smiling while entering a story, it will generate illustrations and dialogue with a bright tone.

[1521] Step 8:

[1522] The server receives the generated manga data (images and text corresponding to a series of scenes) and stores it in a database. At this stage, the basic pages of the manga are formed.

[1523] Step 9:

[1524] The server generates a link or view to display the generated manga data to the user and notifies the user, who can then view the generated manga on their device.

[1525] Step 10:

[1526] Users can use the provided editing interface to modify or add to the manga, for example, by changing the dialogue of characters or replacing backgrounds.

[1527] Step 11:

[1528] The editing interface also automatically suggests facial expressions and lines for characters based on the emotional data obtained by the emotion engine, which users can then modify.

[1529] Step 12:

[1530] The device sends the user's modifications and additions to the server, and after the changes are confirmed in the form or interface, the data is transferred again using JavaScript or Ajax.

[1531] Step 13:

[1532] The server receives the corrections and additional data, integrates it with the existing comic data, updates the comic data in the database, and saves the corrections.

[1533] Step 14:

[1534] The server then displays the updated manga data to the user again, allowing the user to check it with any corrections or additions reflected.

[1535] Step 15:

[1536] If the user wishes to publish in multiple languages, he or she can select the desired translation language in the interface, for example, "English."

[1537] Step 16:

[1538] The device sends a translation request to the server along with information about the selected translation language. The user's selection is communicated to the server using JavaScript or Ajax.

[1539] Step 17:

[1540] The server retrieves the manga data and inputs it into the translation module. First, it extracts the text part of the manga and passes it to the translation engine.

[1541] Step 18:

[1542] The translation module automatically translates manga text into the specified language, using an AI-based translation engine to perform language conversion.

[1543] Step 19:

[1544] The server then incorporates the translated text into the original manga data and saves it again, creating a complete manga data set in the new language.

[1545] Step 20:

[1546] The server displays the translated manga to the user, who can then view the completed multilingual manga on their device.

[1547] Step 21:

[1548] When a user indicates their intention to publish a completed manga, they press the publish button on their device, and a publish request is sent to the server.

[1549] Step 22:

[1550] The device sends a disclosure request to the server, which sends all the data required for disclosure.

[1551] Step 23:

[1552] The server receives the publishing request and uploads the manga data to the publishing platform, along with metadata such as title, summary, and tags.

[1553] Step 24:

[1554] The server performs functions to place advertisements and provide revenue data to users. It embeds advertisements in published comics and reflects revenue information on the dashboard.

[1555] Step 25:

[1556] Users can check their earnings on their device and view how much advertising revenue they are earning through a dashboard.

[1557] The above are the specific processing steps of the system that combines the emotion engine.

[1558] Example 2

[1559] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1560] Traditional manga production requires advanced skills and time, making it difficult for ordinary users to easily create high-quality manga. Furthermore, there was a lack of an automatic generation system with emotion recognition functionality, making it impossible to create content that responded to the user's emotions. Furthermore, there was a lack of automatic generation of multilingual visual representations and post-publication monetization functionality.

[1561] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1562] In this invention, the server includes: a means for a user to input a story; a means for automatically generating visual representations and text based on the story using a generative AI model; a means for providing an interface that allows the user to make corrections and additions; a means including an emotion engine that recognizes the user's emotions and reflects them in the generation process; a means for translating the generated visual representations into multiple languages; and a means for publishing the generated and modified visual representations. This makes it possible to automatically generate high-quality manga that responds to user emotions, publish them in multiple languages, and monetize them without specialized skills.

[1563] "User" refers to a general user who uses the system to input and edit stories.

[1564] A "story" is the story text that the user inputs into the system and is the basis for the visual representation.

[1565] "Generative AI model" refers to an artificial intelligence model that automatically generates visual representations and text based on a story entered by a user.

[1566] "Visual representation" refers to the graphical output, including cartoons and illustrations, automatically generated by generative AI models.

[1567] "Character" refers to text used in visual presentations, including character dialogue and explanatory text.

[1568] "Interface" refers to the screen and operating means that allow users to operate the system, and can be modified and added to.

[1569] The "emotion engine" refers to the part of the system that analyzes the user's facial expressions and voice data to recognize emotions and reflect them in the generation process.

[1570] "Multilingual translation" refers to the process of converting the generated visual and written representations into multiple different languages.

[1571] "Publishing" refers to the act of making the generated and modified visual representations available to the public online or on other platforms.

[1572] This invention is a system that enables users who cannot draw to easily create and publish manga, and is combined with an emotion engine. The system is composed of the following main components: a means for inputting story text, a means for automatically generating visual representations using a generative AI model, an interface for user corrections and additions, a means for translating into multiple languages, a means for publishing the generated and modified visual representations, and an emotion engine that recognizes the user's emotions.

[1573] Story text input

[1574] The user accesses the story input module of the system using a terminal (PC, smartphone, etc.) and inputs a story into the text area. For example, the user inputs a story such as "A boy goes on an adventure to defeat his enemies with magical powers."

[1575] Utilizing the Emotion Engine

[1576] Immediately after the story is sent, the server launches the emotion engine, which analyzes the user's facial expressions and voice data in real time. The emotion engine recognizes emotions such as smile, surprise, and anger. This information is then used in the generative AI model and in the interface for corrections and additions.

[1577] Generative AI Models

[1578] The server inputs the input story and emotion engine data into a generative AI model, which then analyzes the story. Using natural language processing technology, the story is divided into scenes, and character designs, backgrounds, and dialogue are generated while adjusting them based on the user's emotions. For example, illustrations with brighter tones are generated for users who smile a lot.

[1579] User-modified and added interface

[1580] The generated visual representation is displayed to the user from the server. The user can review the displayed visual representation and make corrections or additions as necessary. In this process, character expressions and lines may be automatically suggested based on the emotional data obtained by the emotion engine. The user can make final corrections using this interface, which allows for easy editing with drag-and-drop and click operations.

[1581] Translation Module

[1582] If the user wishes to publish in multiple languages, the server uses a translation module to translate the visual representation into the specified language. This module uses an AI-based translation engine to translate the text portion of the visual representation into other languages. The translated content is then re-integrated to generate multilingual visual representation data.

[1583] Publishing and Monetization

[1584] When a user indicates their intention to publish the completed visual representation, the server uploads the visual representation data to the publishing platform. A monetization function is also provided for this purpose. After publishing, users can check revenue data on a dedicated dashboard. For example, if User A enters a story with a smile, such as "A boy's adventure defeats enemies with magical powers," the generative AI model automatically generates a corresponding bright-toned visual representation. User A then further edits and adds character lines and facial expressions, and publishes the final version in multiple languages. User A can check and collect revenue on the dashboard.

[1585] Examples of prompt statements

[1586] "Please create a light-hearted manga about the adventures of a hero who slays a dragon. Emphasize the joy on the hero's face."

[1587] Through this series of processes, the present invention automates the manga production process, providing a system that allows anyone to easily create, publish, and monetize high-quality visual expressions. By combining it with an emotion engine, it is possible to generate even more appealing content that is in line with the user's emotions.

[1588] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1589] Step 1:

[1590] Story Input

[1591] The user uses a terminal (PC, smartphone, etc.) to access the story input module of the system and input a story. The user enters specific story text into the text area, such as "An adventure in which a boy defeats enemies with the power of magic."

[1592] Input: Story text (e.g. "A boy's adventure in defeating his enemies with magical powers")

[1593] Output: The input story text is sent to the server.

[1594] Specific operations: Open a browser on your device, log in to the system webpage, open the story input module, enter the story in the text area, and click the "Submit" button.

[1595] Step 2:

[1596] Emotional Data Analysis

[1597] The server starts the emotion engine the moment the user submits the story text. The server acquires the user's facial expressions and voice data in real time and analyzes them with the emotion engine.

[1598] Input: User's live camera video and audio data

[1599] Output: Real-time emotion data such as smile, surprise, anger, etc.

[1600] Specific operation: When the server receives the request, it requests permission to access the local camera and microphone device. With the user's permission, it acquires camera footage and audio, and analyzes them using the emotion engine.

[1601] Step 3:

[1602] Automatic manga generation

[1603] The server inputs the input story text and emotion data into a generative AI model to automatically generate a manga. Natural language processing technology is used to divide the story into scenes, and character designs, backgrounds, and dialogue are adjusted according to the user's emotions.

[1604] Input: Story text, emotion data

[1605] Output: Story divided into scenes, generated manga (characters, background, dialogue)

[1606] How it works: The server breaks down the story into scenes, sends them to the AI ​​model, and generates characters and scenes with a brighter tone, including a "smile" prompt, if there is a lot of smiling data.

[1607] Step 4:

[1608] User modifications and additions

[1609] The generated manga is displayed on the user's device from the server. The user can review the displayed manga and modify or add character designs and dialogue. Automatic suggestions are also made based on data from the emotion engine.

[1610] Input: Generated cartoon, emotion data

[1611] Output: Modified cartoon

[1612] Specific operation: The generated manga is displayed on the device, and the user enters editing mode and can change the character design, background, and dialogue using drag-and-drop and click operations.

[1613] Step 5:

[1614] Translation Processing

[1615] If the user desires multilingual publication, the server uses a translation module to translate the visual representation into the specified languages.

[1616] Input: The user's preferred language and visual representation

[1617] Output: Translated visual representation (multilingual)

[1618] What it does: The server passes the text of the manga to an AI-based translation engine, for example, to translate the Japanese manga into English and Chinese, and then re-incorporates the translated text.

[1619] Step 6:

[1620] Publishing and Monetization

[1621] Once the user has decided to publish the completed visual representation, the server uploads the visual representation data to the publishing platform. If necessary, advertisements can be inserted to generate revenue. The user can view revenue data on the dashboard.

[1622] Input: Finished visual representation, monetization request

[1623] Output: Published visual representation, revenue data

[1624] What it does: The server uploads the visual representation to the publishing platform and inserts the necessary ads. Users can view revenue data on the dashboard and understand their revenue status.

[1625] (Application example 2)

[1626] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1627] In recent years, there has been a growing demand in the field of content creation for systems that allow users who are not skilled at drawing to easily create, publish, and monetize high-quality manga. However, conventional systems have had issues with automatically generating content that reflects the user's emotions, and publishing and monetizing content in multiple languages ​​is complicated.

[1628] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for inputting story text, a means for automatically generating illustrations and characters for a manga based on the story text using a generative AI model, an emotion recognition means for analyzing the user's emotions, and a means for adaptively adjusting the generated manga based on the emotion recognition results. This makes it possible to easily generate high-quality content that is in line with the user's emotions, and to publish and monetize it in multiple languages.

[1629] The "story text input means" is an interface device that allows the user to input the text of the story.

[1630] A "generative AI model" is an artificial intelligence algorithm that automatically generates manga illustrations and characters based on input text.

[1631] The "emotion recognition means" is a device that analyzes the user's facial expressions and voice data and recognizes the user's emotional state in real time.

[1632] The "adaptive adjustment means" is a mechanism that dynamically adjusts the generated content based on the user's emotion data obtained by the emotion recognition means.

[1633] The "modification and addition interface" is an operation panel that allows the user to modify and add to the automatically generated comic.

[1634] The "multilingual translation means" is a system that translates automatically generated manga into different specified languages.

[1635] "Publication means" is a platform for publicly disclosing the created and modified manga.

[1636] The "storage and management means" refers to a storage device and management system for permanently storing and managing the generated manga data.

[1637] The "revenue data providing means" is a function that places advertisements and provides generated revenue data to users in real time.

[1638] This invention relates to a system that enables users who are not skilled in drawing to easily create, publish, and monetize manga. This system incorporates emotion recognition means, generates high-quality content that reflects the user's emotions, and supports multilingual publishing and monetization.

[1639] 1. Story text input method

[1640] A user uses a device such as a smartphone or tablet to access a dedicated application and input story text. For example, a user can input a story called "Adventures at a Magic School." This story text is accepted by the system's story text input module.

[1641] 2. Emotion recognition means

[1642] When the server receives the input story text, it uses the device's camera and microphone to analyze the user's facial expressions and voice in real time. Specifically, it uses a facial expression recognition library (e.g., OpenCV) and voice analysis tools to identify the user's emotional state. This emotional data plays an important role in the subsequent manga generation by the generative AI model.

[1643] 3. Generative AI Models

[1644] The server automatically generates manga using a generative AI model (e.g., Stable Diffusion, GPT-3) based on the collected story text and emotion data. This AI model uses natural language processing technology to divide the story text into scenes and adjust the character design, background, and dialogue as it generates them. For example, if the user is smiling, the system generates an illustration with a bright tone.

[1645] 4. Adaptive Adjustment Measures

[1646] The generated manga is sent from the server to the user's device, where the user can review and edit it. As the user makes edits, the system automatically suggests character expressions and lines based on emotion recognition data. The interface allows for intuitive and easy editing using drag-and-drop and click operations.

[1647] 5. Multilingual Translation Tools

[1648] If a user wishes to publish in multiple languages, the server uses a translation engine (e.g., Google Translate, DeepL) to translate the text of the manga into other languages. The translated content is then re-incorporated into the manga, generating multilingual manga data.

[1649] 6. Disclosure Methods

[1650] Users can upload their completed manga to a publishing platform. The system will then publish the manga data and monetize it by inserting advertisements. This revenue data can be viewed in real time on a user-specific dashboard.

[1651] 7. Storage and management measures

[1652] The system stores the generated manga data on a cloud server and manages it permanently, allowing users to access, reuse, and re-edit their past works at any time.

[1653] Prompt Sentence Examples

[1654] Here are some examples of prompts you can enter into a generative AI model:

[1655] The user entered the story text: "Magic School Adventures".

[1656] The emotion engine identified that the user was laughing happily.

[1657] Generate a cartoon scene based on the following criteria:

[1658] Character: A cheerful and energetic student

[1659] Background: Magical school classroom

[1660] Overall tone: bright and fun

[1661] Dialogue: Lines spoken by characters in a fun way

[1662] Scene 1: "First Day at Magic School"

[1663] Scene 2: "Magic Lessons with New Friends"

[1664] Scene 3: "Amazing Magical Experiment"

[1665] In this way, this system enables anyone to easily create high-quality manga, publish it in multiple languages, and monetize it.

[1666] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1667] Step 1: Enter your story text

[1668] A user accesses the application using a device such as a smartphone or tablet. The user inputs (inputs) the text of the story into the story text input module of the application. For example, the user inputs the text "Adventures at the Magic School."

[1669] This text is sent to the backend of the system (output).

[1670] Step 2: Start Recognizing Emotions

[1671] At the same time as the story text is transmitted, the server collects the user's facial expressions and voice in real time using the device's camera and microphone (input).

[1672] The collected data is analyzed using a facial expression recognition library (e.g., OpenCV) and voice analysis tools to identify the user's emotional state (data processing).

[1673] The identified emotion data (output) is used in the next generation process.

[1674] Step 3: Generate manga using generative AI models

[1675] The server inputs the input story text and emotion data into the generative AI model (input).

[1676] Generative AI models (e.g., Stable Diffusion, GPT-3) use natural language processing techniques to divide story text into scenes and generate character designs, backgrounds, and dialogue (data calculations).

[1677] If smiling emotion data is detected, the character and background are adjusted to a brighter tone.

[1678] The generated comic data is sent to the user terminal (output).

[1679] Step 4: User Modifications and Additions

[1680] The user checks the generated manga and makes corrections or additions as necessary (input).

[1681] The system automatically suggests character expressions and lines based on emotion recognition data (data processing).

[1682] Users can easily edit using drag and drop and click operations (specific operations).

[1683] The corrected comic data is resubmitted to the server (output).

[1684] Step 5: Multilingual Translation

[1685] If the user chooses to publish in multiple languages, the server will use a translation engine (e.g., Google Translate, DeepL) to translate the text portion of the manga into the specified language (input and data processing).

[1686] The translated text is then re-incorporated into the manga data, and multilingual manga data is generated (output).

[1687] Step 6: Publish your manga

[1688] When a user indicates their intention to publish the completed manga, the server uploads the manga data to the publishing platform (input and output).

[1689] The publishing platform makes the comic data available to the public and simultaneously inserts advertisements (specific operations).

[1690] The published data can be viewed as revenue on the user's dashboard (data processing).

[1691] Step 7: Store and manage

[1692] The server stores and manages the generated manga data in cloud storage (input and output).

[1693] Users can access the saved manga data at any time and reuse or re-edit it (specific operation).

[1694] By following these steps, users can easily create high-quality, emotive comics, publish them in multiple languages, and monetize them.

[1695] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1696] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1697] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1698] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1699] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1700] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1701] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1702] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1703] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1704] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1705] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1706] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1707] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1708] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1709] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1710] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1711] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1712] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1713] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1714] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1715] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1716] The following is further disclosed regarding the above embodiment.

[1717] (Claim 1)

[1718] a means for inputting story text;

[1719] A means for automatically generating manga illustrations and characters based on the story text using a generative AI model;

[1720] means for providing an interface through which a user can make modifications and additions;

[1721] A means to translate the generated manga into multiple languages,

[1722] a means for publishing the generated and modified cartoons;

[1723] A system including:

[1724] (Claim 2)

[1725] 10. The system of claim 1, further comprising means for storing and managing the generated cartoons.

[1726] (Claim 3)

[1727] 10. The system of claim 1, further comprising means for placing advertisements and providing revenue data to users.

[1728] "Example 1"

[1729] (Claim 1)

[1730] an input device for inputting a story text created by the user;

[1731] A generator that automatically generates manga illustrations and characters based on the story text using a generative AI model;

[1732] a display device that provides an editing interface that allows a user to make modifications and additions to the generated cartoon;

[1733] a translation device that translates the generated manga into multiple languages;

[1734] a publishing device that publishes the generated and modified manga based on a user's specification;

[1735] A system including:

[1736] (Claim 2)

[1737] 10. The system of claim 1, further comprising a storage device for storing and managing the generated cartoons.

[1738] (Claim 3)

[1739] 10. The system of claim 1, further comprising a revenue device that places advertisements and provides revenue data for published comics to users.

[1740] "Application Example 1"

[1741] (Claim 1)

[1742] a means for inputting story text;

[1743] A means for automatically generating manga illustrations and characters based on the story text using a generative AI model;

[1744] means for providing an interface through which a user can make modifications and additions;

[1745] A means to translate the generated manga into multiple languages,

[1746] a means for publishing the generated and modified cartoons;

[1747] A means for supporting a smartphone or head-mounted display;

[1748] A means to control content publishing and monetization;

[1749] A system including:

[1750] (Claim 2)

[1751] 10. The system of claim 1, further comprising means for storing and managing the generated cartoons.

[1752] (Claim 3)

[1753] 10. The system of claim 1, further comprising means for placing advertisements and providing revenue data to users.

[1754] "Example 2: Combining Emotion Engines"

[1755] (Claim 1)

[1756] a means for a user to input a story;

[1757] A means for automatically generating visual representations and text based on the story using a generative AI model;

[1758] means for providing an interface through which a user can make modifications and additions;

[1759] means including an emotion engine for recognizing a user's emotion and reflecting it in the generation process;

[1760] a means for translating the generated visual representation into multiple languages;

[1761] means for publishing the generated and modified visual representation;

[1762] A system including:

[1763] (Claim 2)

[1764] 10. The system of claim 1, further comprising means for storing and managing the generated visual representation.

[1765] (Claim 3)

[1766] 10. The system of claim 1, further comprising means for placing advertisements and providing revenue data to users.

[1767] "Application example 2 when combining emotion engines"

[1768] (Claim 1)

[1769] a means for inputting story text;

[1770] A means for automatically generating manga illustrations and characters based on the story text using a generative AI model;

[1771] emotion recognition means for analyzing the emotion of a user;

[1772] A means for adaptively adjusting the generated cartoon based on the emotion recognition result;

[1773] means for providing an interface through which a user can make modifications and additions;

[1774] A means to translate the generated manga into multiple languages,

[1775] a means for publishing the generated and modified cartoons;

[1776] A system including:

[1777] (Claim 2)

[1778] 10. The system of claim 1, further comprising means for storing and managing the generated cartoons.

[1779] (Claim 3)

[1780] 10. The system of claim 1, further comprising means for placing advertisements and providing revenue data to users. [Explanation of symbols]

[1781] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for inputting story text; A means for automatically generating manga illustrations and characters based on the story text using a generative AI model; means for providing an interface through which a user can make modifications and additions; A means to translate the generated manga into multiple languages, a means for publishing the generated and modified cartoons; A system including:

2. The system of claim 1 further comprising means for storing and managing the generated cartoons.

3. The system of claim 1 further comprising means for placing advertisements and providing revenue data to users.

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